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Shackleton D, Memon FA, Nichols G, Phalkey R, Chen AS. Mechanisms of cholera transmission via environment in India and Bangladesh: state of the science review. REVIEWS ON ENVIRONMENTAL HEALTH 2024; 39:313-329. [PMID: 36639850 DOI: 10.1515/reveh-2022-0201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 12/10/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVES Cholera has a long history in India and Bangladesh, the region where six out of the past seven global pandemics have been seeded. The changing climate and growing population have led to global cholera cases remaining high despite a consistent improvement in the access to clean water and sanitation. We aim to provide a holistic overview of variables influencing environmental cholera transmission within the context of India and Bangladesh, with a focus on the mechanisms by which they act. CONTENT We identified 56 relevant texts (Bangladesh n = 40, India n = 7, Other n = 5). The results of the review found that cholera transmission is associated with several socio-economic and environmental factors, each associated variable is suggested to have at least one mediating mechanism. Increases in ambient temperature and coastal sea surface temperature support cholera transmission via increases in plankton and a preference of Vibrio cholerae for warmer waters. Increased rainfall can potentially support or reduce transmission via several mechanisms. SUMMARY AND OUTLOOK Common issues in the literature are co-variance of seasonal factors, limited access to high quality cholera data, high research bias towards research in Dhaka and Matlab (Bangladesh). A specific and detailed understanding of the relationship between SST and cholera incidence remains unclear.
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Affiliation(s)
- Debbie Shackleton
- College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK
| | - Fayyaz A Memon
- College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK
| | - Gordon Nichols
- European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Truro, Cornwall, UK
- University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK
| | - Revati Phalkey
- Climate Change and Health Group, UK Health Security Agency, London, UK
- Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany
- Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK
| | - Albert S Chen
- College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK
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2
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Anteneh LM, Lokonon BE, Kakaï RG. Modelling techniques in cholera epidemiology: A systematic and critical review. Math Biosci 2024; 373:109210. [PMID: 38777029 DOI: 10.1016/j.mbs.2024.109210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 05/25/2024]
Abstract
Diverse modelling techniques in cholera epidemiology have been developed and used to (1) study its transmission dynamics, (2) predict and manage cholera outbreaks, and (3) assess the impact of various control and mitigation measures. In this study, we carry out a critical and systematic review of various approaches used for modelling the dynamics of cholera. Also, we discuss the strengths and weaknesses of each modelling approach. A systematic search of articles was conducted in Google Scholar, PubMed, Science Direct, and Taylor & Francis. Eligible studies were those concerned with the dynamics of cholera excluding studies focused on models for cholera transmission in animals, socio-economic factors, and genetic & molecular related studies. A total of 476 peer-reviewed articles met the inclusion criteria, with about 40% (32%) of the studies carried out in Asia (Africa). About 52%, 21%, and 9%, of the studies, were based on compartmental (e.g., SIRB), statistical (time series and regression), and spatial (spatiotemporal clustering) models, respectively, while the rest of the analysed studies used other modelling approaches such as network, machine learning and artificial intelligence, Bayesian, and agent-based approaches. Cholera modelling studies that incorporate vector/housefly transmission of the pathogen are scarce and a small portion of researchers (3.99%) considers the estimation of key epidemiological parameters. Vaccination only platform was utilized as a control measure in more than half (58%) of the studies. Research productivity in cholera epidemiological modelling studies have increased in recent years, but authors used diverse range of models. Future models should consider incorporating vector/housefly transmission of the pathogen and on the estimation of key epidemiological parameters for the transmission of cholera dynamics.
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Affiliation(s)
- Leul Mekonnen Anteneh
- Laboratoire de Biomathématiques et d'Estimations Forestières, University of Abomey-Calavi, Cotonou, Benin.
| | - Bruno Enagnon Lokonon
- Laboratoire de Biomathématiques et d'Estimations Forestières, University of Abomey-Calavi, Cotonou, Benin
| | - Romain Glèlè Kakaï
- Laboratoire de Biomathématiques et d'Estimations Forestières, University of Abomey-Calavi, Cotonou, Benin
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3
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Maloney P, Kompaniyets L, Yusuf H, Bonilla L, Figueroa C, Garcia M. The effects of policy changes and human mobility on the COVID-19 epidemic in the Dominican Republic, 2020-2021. Prev Med Rep 2023; 36:102459. [PMID: 37840596 PMCID: PMC10568125 DOI: 10.1016/j.pmedr.2023.102459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 10/03/2023] [Accepted: 10/04/2023] [Indexed: 10/17/2023] Open
Abstract
Recent advances in technology can be leveraged to enhance public health research and practice. This study aimed to assess the effects of mobility and policy changes on COVID-19 case growth and the effects of policy changes on mobility using data from Google Mobility Reports, information on public health policy, and COVID-19 testing results. Multiple bivariate regression analyses were conducted to address the study objectives. Policies designed to limit mobility led to decreases in mobility in public areas. These policies also decreased COVID-19 case growth. Conversely, policies that did not restrict mobility led to increases in mobility in public areas and led to increases in COVID-19 case growth. Mobility increases in public areas corresponded to increases in COVID-19 case growth, while concentration of mobility in residential areas corresponded to decreases in COVID-19 case growth. Overall, restrictive policies were effective in decreasing COVID-19 incidence in the Dominican Republic, while permissive policies led to increases in COVID-19 incidence.
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Affiliation(s)
- Patrick Maloney
- Centers for Disease Control and Prevention, Dominican Republic
| | - Lyudmyla Kompaniyets
- Centers for Disease Control and Prevention, Division of Nutrition, Physical Activity and Obesity, Obesity Prevention and Control Branch, Atlanta, GA, United States
| | - Hussain Yusuf
- Centers for Disease Control and Prevention, Division of Health Information and Surveillance, Partnerships and Evaluation Branch, Atlanta, GA, United States
| | - Luis Bonilla
- Centers for Disease Control and Prevention, Dominican Republic
| | - Carmen Figueroa
- Centers for Disease Control and Prevention, Dominican Republic
| | - Macarena Garcia
- Centers for Disease Control and Prevention, Dominican Republic
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4
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Delussu F, Tizzoni M, Gauvin L. The limits of human mobility traces to predict the spread of COVID-19: A transfer entropy approach. PNAS NEXUS 2023; 2:pgad302. [PMID: 37811338 PMCID: PMC10558401 DOI: 10.1093/pnasnexus/pgad302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 08/17/2023] [Indexed: 10/10/2023]
Abstract
Mobile phone data have been widely used to model the spread of COVID-19; however, quantifying and comparing their predictive value across different settings is challenging. Their quality is affected by various factors and their relationship with epidemiological indicators varies over time. Here, we adopt a model-free approach based on transfer entropy to quantify the relationship between mobile phone-derived mobility metrics and COVID-19 cases and deaths in more than 200 European subnational regions. Using multiple data sources over a one-year period, we found that past knowledge of mobility does not systematically provide statistically significant information on COVID-19 spread. Our approach allows us to determine the best metric for predicting disease incidence in a particular location, at different spatial scales. Additionally, we identify geographic and demographic factors, such as users' coverage and commuting patterns, that explain the (non)observed relationship between mobility and epidemic patterns. Our work provides epidemiologists and public health officials with a general-not limited to COVID-19-framework to evaluate the usefulness of human mobility data in responding to epidemics.
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Affiliation(s)
- Federico Delussu
- ISI Foundation, via Chisola 5, 10126 Torino, Italy
- Department of Applied Mathematics and Computer Science, DTU, Richard Petersens Plads, DK-2800 Copenhagen, Denmark
| | - Michele Tizzoni
- ISI Foundation, via Chisola 5, 10126 Torino, Italy
- Department of Sociology and Social Research, University of Trento, via Verdi 26, I-38122 Trento, Italy
| | - Laetitia Gauvin
- ISI Foundation, via Chisola 5, 10126 Torino, Italy
- UMR 215 PRODIG, Institute for Research on Sustainable Development - IRD, 5 cours des Humanités, F-93 322 Aubervilliers Cedex, France
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5
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Mueller V, Páez-Bernal C, Gray C, Grépin K. The Gendered Consequences of COVID-19 for Internal Migration. POPULATION RESEARCH AND POLICY REVIEW 2023; 42:60. [PMID: 37397235 PMCID: PMC10307700 DOI: 10.1007/s11113-023-09809-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 06/15/2023] [Indexed: 07/04/2023]
Abstract
Scant evidence exists to identify the effects of the pandemic on migrant women and the unique barriers on employment they endure. We merge longitudinal data from mobile phone surveys with subnational data on COVID cases to examine whether women were left more immobile and vulnerable to health risks, relative to men, during the pandemic in Kenya and Nigeria. Each survey interviewed approximately 2000 men and women over three rounds (November 2020-January 2021, March-April 2021, November 2021-January 2022). Linear regression analysis reveals internal migrants are no more vulnerable to knowing someone in their network with COVID. Rather, rural migrant women in Kenya and Nigeria were less vulnerable to transmission through their network, perhaps related to the possible wealth accumulation from migration or acquired knowledge of averting health risks from previous destinations. Per capita exposure to COVID cases hinders the inter-regional migration of women in both countries. Exposure to an additional COVID case per 10,000 people resulted in a decline in women's interregional migration by 6 and 2 percentage points in Kenya and Nigeria, respectively.
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Affiliation(s)
- Valerie Mueller
- School of Politics and Global Studies, Arizona State University, Tempe, USA
- International Food Policy Research Institute, Washington, DC USA
| | - Camila Páez-Bernal
- School of Politics and Global Studies, Arizona State University, Tempe, USA
| | - Clark Gray
- Department of Geography, University of North Carolina, Chapel Hill, USA
| | - Karen Grépin
- School of Public Health, University of Hong Kong, Hong Kong, China
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6
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Ayling S, Milusheva S, Maidei Kashangura F, Hoo YR, Sturrock H, Joseph G. A stitch in time: The importance of water and sanitation services (WSS) infrastructure maintenance for cholera risk. A geospatial analysis in Harare, Zimbabwe. PLoS Negl Trop Dis 2023; 17:e0011353. [PMID: 37327203 DOI: 10.1371/journal.pntd.0011353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 05/03/2023] [Indexed: 06/18/2023] Open
Abstract
Understanding the factors associated with cholera outbreaks is an integral part of designing better approaches to mitigate their impact. Using a rich set of georeferenced case data from the cholera epidemic that occurred in Harare from September 2018 to January 2019, we apply spatio-temporal modelling to better understand how the outbreak unfolded and the factors associated with higher risk of being a reported case. Using Call Detail Records (CDR) to estimate weekly population movement of the community throughout the city, results suggest that broader human movement (not limited to infected agents) helps to explain some of the spatio-temporal patterns of cases observed. In addition, results highlight a number of socio-demographic risk factors and suggest that there is a relationship between cholera risk and water infrastructure. The analysis shows that populations living close to the sewer network, with high access to piped water are associated with at higher risk. One possible explanation for this observation is that sewer bursts led to the contamination of the piped water network. This could have turned access to piped water, usually assumed to be associated with reduced cholera risk, into a risk factor itself. Such events highlight the importance of maintenance in the provision of SDG improved water and sanitation infrastructure.
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Affiliation(s)
- Sophie Ayling
- Water Global Practice, World Bank Group, Washington DC, United States of America
| | - Sveta Milusheva
- Development Impact Evaluation Unit (DIME), World Bank Group, Washington DC, United States of America
| | | | - Yi Rong Hoo
- Water Global Practice, World Bank Group, Washington DC, United States of America
| | | | - George Joseph
- Water Global Practice, World Bank Group, Washington DC, United States of America
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7
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Chaudhuri S, Srivastava A. Network approach to understand biological systems: From single to multilayer networks. J Biosci 2022. [DOI: 10.1007/s12038-022-00285-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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8
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Rana A, Mukherjee T, Adak S. Mobility patterns and COVID growth: Moderating role of country culture. INTERNATIONAL JOURNAL OF INTERCULTURAL RELATIONS : IJIR 2022; 89:124-151. [PMID: 35761827 PMCID: PMC9220803 DOI: 10.1016/j.ijintrel.2022.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 01/10/2022] [Accepted: 06/01/2022] [Indexed: 06/15/2023]
Abstract
The COVID-19 pandemic has resulted in countries reacting differently to an ongoing crisis situation. Latent to this reaction mechanism is the inherent cultural characteristics of each society resulting in differential responses to epidemic spread. Epidemiological studies have confirmed the positive effect of population mobility on the growth of infection. However, the effect of culture on indigenous mobility patterns during pandemics needs further investigation. This study aims to bridge this gap by exploring the moderating role of country culture on the relationship between population mobility and growth of CoVID-19. Hofstede's cultural factors; power distance, individualism/collectivism, masculinity/femininity, uncertainty avoidance, long-term and short-term orientation are hypothesised to moderate the effect of mobility on the reproduction number (R) of COVID-19. Panel regression model, using mobility data and number of confirmed cases across 95 countries for a period of 170 days has been preferred to test the hypotheses. The results are further substantiated using slope analysis and Johnson-Neyman technique. The findings suggest that as power distance, individualism and long-term orientation scores increase, the impact of mobility on epidemic growth decreases. However, masculinity scores in a society have an opposite moderating impact on epidemic growth rate. These Hofstede factors act as quasi moderators affecting mobility and epidemic growth. Similar conclusions could be not be confirmed for uncertainty avoidance. Cross-cultural impact, as elucidated by this study, forms a crucial element in policy formulation on epidemic control by indigenous Governing bodies.
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Affiliation(s)
- Arunima Rana
- Indian Institute of Foreign Trade (IIFT), New Delhi, India
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9
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Pessoa Colombo V, Chenal J, Koné B, Bosch M, Utzinger J. Using Open-Access Data to Explore Relations between Urban Landscapes and Diarrhoeal Diseases in Côte d’Ivoire. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19137677. [PMID: 35805337 PMCID: PMC9265306 DOI: 10.3390/ijerph19137677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 06/17/2022] [Accepted: 06/21/2022] [Indexed: 02/01/2023]
Abstract
Unlike water and sanitation infrastructures or socio-economic indicators, landscape features are seldomly considered as predictors of diarrhoea. In contexts of rapid urbanisation and changes in the physical environment, urban planners and public health managers could benefit from a deeper understanding of the relationship between landscape patterns and health outcomes. We conducted an ecological analysis based on a large ensemble of open-access data to identify specific landscape features associated with diarrhoea. Designed as a proof-of-concept study, our research focused on Côte d’Ivoire. This analysis aimed to (i) build a framework strictly based on open-access data and open-source software to investigate diarrhoea risk factors originating from the physical environment and (ii) understand whether different types and forms of urban settlements are associated with different prevalence rates of diarrhoea. We advanced landscape patterns as variables of exposure and tested their association with the prevalence of diarrhoea among children under the age of five years through multiple regression models. A specific urban landscape pattern was significantly associated with diarrhoea. We conclude that, while the improvement of water, sanitation, and hygiene infrastructures is crucial to prevent diarrhoeal diseases, the health benefits of such improvements may be hampered if the overall physical environment remains precarious.
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Affiliation(s)
- Vitor Pessoa Colombo
- School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland; (J.C.); (M.B.)
- Correspondence:
| | - Jérôme Chenal
- School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland; (J.C.); (M.B.)
| | - Brama Koné
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire;
| | - Martí Bosch
- School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland; (J.C.); (M.B.)
| | - Jürg Utzinger
- Swiss Tropical and Public Health Institute, 4123 Allschwil, Switzerland;
- University of Basel, 4001 Basel, Switzerland
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10
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Trevisin C, Lemaitre JC, Mari L, Pasetto D, Gatto M, Rinaldo A. Epidemicity of cholera spread and the fate of infection control measures. J R Soc Interface 2022; 19:20210844. [PMID: 35259956 PMCID: PMC8905172 DOI: 10.1098/rsif.2021.0844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
The fate of ongoing infectious disease outbreaks is predicted through reproduction numbers, defining the long-term establishment of the infection, and epidemicity indices, tackling the reactivity of the infectious pool to new contagions. Prognostic metrics of unfolding outbreaks are of particular importance when designing adaptive emergency interventions facing real-time assimilation of epidemiological evidence. Our aim here is twofold. First, we propose a novel form of the epidemicity index for the characterization of cholera epidemics in spatial models of disease spread. Second, we examine in hindsight the survey of infections, treatments and containment measures carried out for the now extinct 2010–2019 Haiti cholera outbreak, to suggest that magnitude and timing of non-pharmaceutical and vaccination interventions imply epidemiological responses recapped by the evolution of epidemicity indices. Achieving negative epidemicity greatly accelerates fading of infections and thus proves a worthwhile target of containment measures. We also show that, in our model, effective reproduction numbers and epidemicity indices are explicitly related. Therefore, providing an upper bound to the effective reproduction number (significantly lower than the unit threshold) warrants negative epidemicity and, in turn, a rapidly fading outbreak preventing coalescence of sparse local sub-threshold flare-ups.
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Affiliation(s)
- Cristiano Trevisin
- Laboratory of Ecohydrology ENAC/IIE/ECHO, École polytechinque fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Joseph C Lemaitre
- Laboratory of Ecohydrology ENAC/IIE/ECHO, École polytechinque fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Lorenzo Mari
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy
| | - Damiano Pasetto
- Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca' Foscari Venezia, Venezia 30172, Italy
| | - Marino Gatto
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy
| | - Andrea Rinaldo
- Laboratory of Ecohydrology ENAC/IIE/ECHO, École polytechinque fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland.,Dipartimento ICEA, Università degli studi di Padova, Padova 35131, Italy
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11
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Charnley GEC, Kelman I, Murray KA. Drought-related cholera outbreaks in Africa and the implications for climate change: a narrative review. Pathog Glob Health 2022; 116:3-12. [PMID: 34602024 PMCID: PMC8812730 DOI: 10.1080/20477724.2021.1981716] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Africa has historically seen several periods of prolonged and extreme droughts across the continent, causing food insecurity, exacerbating social inequity and frequent mortality. A known consequence of droughts and their associated risk factors are infectious disease outbreaks, which are worsened by malnutrition, poor access to water, sanitation and hygiene and population displacement. Cholera is a potential causative agent of such outbreaks. Africa has the highest global cholera burden, several drought-prone regions and high levels of inequity. Despite this, research on cholera and drought in Africa is lacking. Here, we review available research on drought-related cholera outbreaks in Africa and identify a variety of potential mechanisms through which these outbreaks occurred, including poor access to water, marginalization of refugees and nomadic populations, expansion of informal urban settlements and demographic risks. Future climate change may alter precipitation, temperature and drought patterns, resulting in more extremes, although these changes are likely to be spatially heterogeneous. Despite high uncertainty in future drought projections, increases in drought frequency and/or durations have the potential to alter these related outbreaks into the future, potentially increasing cholera burden in the absence of countermeasures (e.g. improved sanitation infrastructure). To enable effective planning for a potentially more drought-prone Africa, inequity must be addressed, research on the health implications of drought should be enhanced, and better drought diplomacy is required to improve drought resilience under climate change.
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Affiliation(s)
- Gina E. C. Charnley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Ilan Kelman
- University of Agder, Kristiansand, Norway
- Institute for Global Health, Faculty of Population Health, University College London, London, UK
- Institute for Risk and Disaster Reduction, Faculty of Mathematical and Physical Sciences, University College London, London, UK
| | - Kris A. Murray
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
- Mrc Unit the Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia
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12
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Markwalter CF, Menya D, Wesolowski A, Esimit D, Lokoel G, Kipkoech J, Freedman E, Sumner KM, Abel L, Ambani G, Meredith HR, Taylor SM, Obala AA, O'Meara WP. Plasmodium falciparum importation does not sustain malaria transmission in a semi-arid region of Kenya. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0000807. [PMID: 36962553 PMCID: PMC10021402 DOI: 10.1371/journal.pgph.0000807] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/17/2022] [Indexed: 11/19/2022]
Abstract
Human movement impacts the spread and transmission of infectious diseases. Recently, a large reservoir of Plasmodium falciparum malaria was identified in a semi-arid region of northwestern Kenya historically considered unsuitable for malaria transmission. Understanding the sources and patterns of transmission attributable to human movement would aid in designing and targeting interventions to decrease the unexpectedly high malaria burden in the region. Toward this goal, polymorphic parasite genes (ama1, csp) in residents and passengers traveling to Central Turkana were genotyped by amplicon deep sequencing. Genotyping and epidemiological data were combined to assess parasite importation. The contribution of travel to malaria transmission was estimated by modelling case reproductive numbers inclusive and exclusive of travelers. P. falciparum was detected in 6.7% (127/1891) of inbound passengers, including new haplotypes which were later detected in locally-transmitted infections. Case reproductive numbers approximated 1 and did not change when travelers were removed from transmission networks, suggesting that transmission is not fueled by travel to the region but locally endemic. Thus, malaria is not only prevalent in Central Turkana but also sustained by local transmission. As such, interrupting importation is unlikely to be an effective malaria control strategy on its own, but targeting interventions locally has the potential to drive down transmission.
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Affiliation(s)
| | - Diana Menya
- School of Public Health, Moi University College of Health Sciences, Eldoret, Kenya
| | - Amy Wesolowski
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Daniel Esimit
- Department of Health Services and Sanitation, Turkana County, Kenya
| | - Gilchrist Lokoel
- Department of Health Services and Sanitation, Turkana County, Kenya
| | - Joseph Kipkoech
- Academic Model Providing Access to Healthcare, Eldoret, Kenya
| | - Elizabeth Freedman
- Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Kelsey M Sumner
- Duke University School of Medicine, Durham, North Carolina, United States of America
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Lucy Abel
- Academic Model Providing Access to Healthcare, Eldoret, Kenya
| | - George Ambani
- Academic Model Providing Access to Healthcare, Eldoret, Kenya
| | - Hannah R Meredith
- Duke Global Health Institute, Durham, North Carolina, United States of America
| | - Steve M Taylor
- Duke Global Health Institute, Durham, North Carolina, United States of America
- Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Andrew A Obala
- School of Medicine, Moi University College of Health Sciences, Eldoret, Kenya
| | - Wendy P O'Meara
- Duke Global Health Institute, Durham, North Carolina, United States of America
- Duke University School of Medicine, Durham, North Carolina, United States of America
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13
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Kluge L, Schewe J. Evaluation and extension of the radiation model for internal migration. Phys Rev E 2021; 104:054311. [PMID: 34942836 DOI: 10.1103/physreve.104.054311] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 11/11/2021] [Indexed: 11/07/2022]
Abstract
Human migration is often studied using gravity models. These models, however, have known limitations, including analytic inconsistencies and a dependence on empirical data to calibrate multiple parameters for the region of interest. Overcoming these limitations, the radiation model has been proposed as an alternative, universal approach to predicting different forms of human mobility, but has not been adopted for studying migration. Here we show, using data on within-country migration from the USA and Mexico, that the radiation model systematically underpredicts long-range moves, while the traditional gravity model performs well for large distances. The universal opportunity model, an extension of the radiation model, shows an improved fit of long-range moves compared to the original radiation model, but at the cost of introducing two additional parameters. We propose a more parsimonious extension of the radiation model that introduces a single parameter. We demonstrate that it fits the data over the full distance spectrum and also-unlike the universal opportunity model-preserves the analytical property of the original radiation model of being equivalent to a gravity model in the limit of a uniform population distribution.
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Affiliation(s)
- Lucas Kluge
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany and Institute of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Strasse 24/25, 14476 Potsdam, Germany
| | - Jacob Schewe
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, D-14412 Potsdam, Germany
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14
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Exploring relationships between drought and epidemic cholera in Africa using generalised linear models. BMC Infect Dis 2021; 21:1177. [PMID: 34809609 PMCID: PMC8609751 DOI: 10.1186/s12879-021-06856-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 11/08/2021] [Indexed: 11/18/2022] Open
Abstract
Background Temperature and precipitation are known to affect Vibrio cholerae outbreaks. Despite this, the impact of drought on outbreaks has been largely understudied. Africa is both drought and cholera prone and more research is needed in Africa to understand cholera dynamics in relation to drought. Methods Here, we analyse a range of environmental and socioeconomic covariates and fit generalised linear models to publicly available national data, to test for associations with several indices of drought and make cholera outbreak projections to 2070 under three scenarios of global change, reflecting varying trajectories of CO2 emissions, socio-economic development, and population growth. Results The best-fit model implies that drought is a significant risk factor for African cholera outbreaks, alongside positive effects of population, temperature and poverty and a negative effect of freshwater withdrawal. The projections show that following stringent emissions pathways and expanding sustainable development may reduce cholera outbreak occurrence in Africa, although these changes were spatially heterogeneous. Conclusions Despite an effect of drought in explaining recent cholera outbreaks, future projections highlighted the potential for sustainable development gains to offset drought-related impacts on cholera risk. Future work should build on this research investigating the impacts of drought on cholera on a finer spatial scale and potential non-linear relationships, especially in high-burden countries which saw little cholera change in the scenario analysis. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06856-4.
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15
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Yuan B, Lee H, Nishiura H. Analysis of international traveler mobility patterns in Tokyo to identify geographic foci of dengue fever risk. Theor Biol Med Model 2021; 18:17. [PMID: 34602095 PMCID: PMC8487561 DOI: 10.1186/s12976-021-00149-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/21/2021] [Indexed: 11/10/2022] Open
Abstract
Travelers play a role in triggering epidemics of imported dengue fever because they can carry the virus to other countries during the incubation period. If a traveler carrying dengue virus visits open green space and is bitten by mosquitoes, a local outbreak can ensue. In the present study, we aimed to understand the movement patterns of international travelers in Tokyo using mobile phone data, with the goal of identifying geographical foci of dengue transmission. We analyzed datasets based on mobile phone access to WiFi systems and measured the spatial distribution of international visitors in Tokyo on two specific dates (one weekday in July 2017 and another weekday in August 2017). Mobile phone users were classified by nationality into three groups according to risk of dengue transmission. Sixteen national parks were selected based on their involvement in a 2014 dengue outbreak and abundance of Aedes mosquitoes. We found that not all national parks were visited by international travelers and that visits to cemeteries were very infrequent. We also found that travelers from countries with high dengue prevalence were less likely to visit national parks compared with travelers from dengue-free countries. Travelers from countries with sporadic dengue cases and countries with regional transmission tended to visit common destinations. By contrast, the travel footprints of visitors from countries with continuous dengue transmission were focused on non-green spaces. Entomological surveillance in Tokyo has been restricted to national parks since the 2014 dengue outbreak. However, our results indicate that areas subject to surveillance should include both public and private green spaces near tourist sites.
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Affiliation(s)
- Baoyin Yuan
- Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido, 060-8638, Japan.,CREST, Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama, 332-0012, Japan.,School of Mathematics, South China University of Technology, 381 Wushan Rd, Tianhe District, Guangzhou, China
| | - Hyojung Lee
- Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido, 060-8638, Japan.,CREST, Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama, 332-0012, Japan.,Department of Statistics, Kyungpook National University, Daegu, 41566, South Korea
| | - Hiroshi Nishiura
- Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido, 060-8638, Japan. .,CREST, Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama, 332-0012, Japan. .,Kyoto University School of Public Health, Yoshidakonoecho, Sakyoku, Kyoto, 6068501, Japan.
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16
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Dowling WB, Van der Westhuyzen M, Haumann M, Reddy K. Non-toxigenic Vibrio cholerae non-O1/non-O139 pseudo-bacteraemia in a neonate: A case report. S Afr J Infect Dis 2021. [DOI: 10.4102/sajid.v36i1.263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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17
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Farzanehfar A, Houssiau F, de Montjoye YA. The risk of re-identification remains high even in country-scale location datasets. PATTERNS (NEW YORK, N.Y.) 2021; 2:100204. [PMID: 33748793 PMCID: PMC7961185 DOI: 10.1016/j.patter.2021.100204] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/27/2020] [Accepted: 01/07/2021] [Indexed: 11/30/2022]
Abstract
Although anonymous data are not considered personal data, recent research has shown how individuals can often be re-identified. Scholars have argued that previous findings apply only to small-scale datasets and that privacy is preserved in large-scale datasets. Using 3 months of location data, we (1) show the risk of re-identification to decrease slowly with dataset size, (2) approximate this decrease with a simple model taking into account three population-wide marginal distributions, and (3) prove that unicity is convex and obtain a linear lower bound. Our estimates show that 93% of people would be uniquely identified in a dataset of 60M people using four points of auxiliary information, with a lower bound at 22%. This lower bound increases to 87% when five points are available. Taken together, our results show how the privacy of individuals is very unlikely to be preserved even in country-scale location datasets.
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Affiliation(s)
- Ali Farzanehfar
- Department of Computing, Imperial College London, London SW7 2AZ, UK
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18
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Scaling of contact networks for epidemic spreading in urban transit systems. Sci Rep 2021; 11:4408. [PMID: 33623098 PMCID: PMC7902662 DOI: 10.1038/s41598-021-83878-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 01/19/2021] [Indexed: 01/02/2023] Open
Abstract
Improved mobility not only contributes to more intensive human activities but also facilitates the spread of communicable disease, thus constituting a major threat to billions of urban commuters. In this study, we present a multi-city investigation of communicable diseases percolating among metro travelers. We use smart card data from three megacities in China to construct individual-level contact networks, based on which the spread of disease is modeled and studied. We observe that, though differing in urban forms, network layouts, and mobility patterns, the metro systems of the three cities share similar contact network structures. This motivates us to develop a universal generation model that captures the distributions of the number of contacts as well as the contact duration among individual travelers. This model explains how the structural properties of the metro contact network are associated with the risk level of communicable diseases. Our results highlight the vulnerability of urban mass transit systems during disease outbreaks and suggest important planning and operation strategies for mitigating the risk of communicable diseases.
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19
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Li J, Manitz J, Bertuzzo E, Kolaczyk ED. Sensor-based localization of epidemic sources on human mobility networks. PLoS Comput Biol 2021; 17:e1008545. [PMID: 33503024 PMCID: PMC7870066 DOI: 10.1371/journal.pcbi.1008545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 02/08/2021] [Accepted: 11/17/2020] [Indexed: 11/18/2022] Open
Abstract
We investigate the source detection problem in epidemiology, which is one of the most important issues for control of epidemics. Mathematically, we reformulate the problem as one of identifying the relevant component in a multivariate Gaussian mixture model. Focusing on the study of cholera and diseases with similar modes of transmission, we calibrate the parameters of our mixture model using human mobility networks within a stochastic, spatially explicit epidemiological model for waterborne disease. Furthermore, we adopt a Bayesian perspective, so that prior information on source location can be incorporated (e.g., reflecting the impact of local conditions). Posterior-based inference is performed, which permits estimates in the form of either individual locations or regions. Importantly, our estimator only requires first-arrival times of the epidemic by putative observers, typically located only at a small proportion of nodes. The proposed method is demonstrated within the context of the 2000-2002 cholera outbreak in the KwaZulu-Natal province of South Africa. Tracking the source of an epidemic outbreak is of crucial importance as it allows for identification of communities where control efforts should be focused for both short and long-term management and control of the disease. However, such identification is often problematic, time-consuming, and data-intensive. Recently network-based analysis approaches have been established for source detection to account for complex modern spreading, driven substantially by human mobility. Here we develop a probabilistic framework for waterborne disease, that allows investigators to infer the community or the region sparking an outbreak based on a sparse surveillance network. The framework can integrate prior information on the likelihood of a community being the source, for instance as a function of population size or hygiene conditions. Furthermore, we assign an accuracy measure to the resulting source estimate, which is crucial for its practical usability. We test the method in the context of the 2000-2002 cholera outbreak in the KwaZulu-Natal province with promising results. Moreover, we outline a series of guidelines in terms of data needs and preliminary operations to implement the proposed framework in practice.
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Affiliation(s)
- Jun Li
- Department of Mathematics & Statistics, Boston University, Boston, MA, United States of America
| | - Juliane Manitz
- Department of Mathematics & Statistics, Boston University, Boston, MA, United States of America
| | - Enrico Bertuzzo
- Dipartimento di Scienze Ambientali, Informatica e Statistica, University of Venice Cà Foscari, Italy
| | - Eric D. Kolaczyk
- Department of Mathematics & Statistics, Boston University, Boston, MA, United States of America
- * E-mail:
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20
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Patil R, Dave R, Patel H, Shah VM, Chakrabarti D, Bhatia U. Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting. APPLIED NETWORK SCIENCE 2021; 6:4. [PMID: 33457497 PMCID: PMC7803387 DOI: 10.1007/s41109-020-00346-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 12/21/2020] [Indexed: 05/24/2023]
Abstract
BACKGROUND The dense social contact networks and high mobility in congested urban areas facilitate the rapid transmission of infectious diseases. Typical mechanistic epidemiological models are either based on uniform mixing with ad-hoc contact processes or need real-time or archived population mobility data to simulate the social networks. However, the rapid and global transmission of the novel coronavirus (SARS-CoV-2) has led to unprecedented lockdowns at global and regional scales, leaving the archived datasets to limited use. FINDINGS While it is often hypothesized that population density is a significant driver in disease propagation, the disparate disease trajectories and infection rates exhibited by the different cities with comparable densities require a high-resolution description of the disease and its drivers. In this study, we explore the impact of creation of containment zones on travel patterns within the city. Further, we use a dynamical network-based infectious disease model to understand the key drivers of disease spread at sub-kilometer scales demonstrated in the city of Ahmedabad, India, which has been classified as a SARS-CoV-2 hotspot. We find that in addition to the contact network and population density, road connectivity patterns and ease of transit are strongly correlated with the rate of transmission of the disease. Given the limited access to real-time traffic data during lockdowns, we generate road connectivity networks using open-source imageries and travel patterns from open-source surveys and government reports. Within the proposed framework, we then analyze the relative merits of social distancing, enforced lockdowns, and enhanced testing and quarantining mitigating the disease spread. SCOPE Our results suggest that the declaration of micro-containment zones within the city with high road network density combined with enhanced testing can help in containing the outbreaks until clinical interventions become available.
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Affiliation(s)
- Rohan Patil
- Discipline of Computer Science and Engineering, Indian Institute of Technology, Gandhinagar, India
| | - Raviraj Dave
- Discipline of Civil Engineering, Indian Institute of Technology, Gandhinagar, India
| | - Harsh Patel
- Discipline of Computer Science and Engineering, Indian Institute of Technology, Gandhinagar, India
| | - Viraj M. Shah
- Discipline of Mechanical Engineering, Indian Institute of Technology, Gandhinagar, India
| | | | - Udit Bhatia
- Discipline of Civil Engineering, Indian Institute of Technology, Gandhinagar, India
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21
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Mo B, Feng K, Shen Y, Tam C, Li D, Yin Y, Zhao J. Modeling epidemic spreading through public transit using time-varying encounter network. TRANSPORTATION RESEARCH. PART C, EMERGING TECHNOLOGIES 2021; 122:102893. [PMID: 33519128 PMCID: PMC7832029 DOI: 10.1016/j.trc.2020.102893] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 10/29/2020] [Accepted: 11/21/2020] [Indexed: 05/04/2023]
Abstract
Passenger contact in public transit (PT) networks can be a key mediate in the spreading of infectious diseases. This paper proposes a time-varying weighted PT encounter network to model the spreading of infectious diseases through the PT systems. Social activity contacts at both local and global levels are also considered. We select the epidemiological characteristics of coronavirus disease 2019 (COVID-19) as a case study along with smart card data from Singapore to illustrate the model at the metropolitan level. A scalable and lightweight theoretical framework is derived to capture the time-varying and heterogeneous network structures, which enables to solve the problem at the whole population level with low computational costs. Different control policies from both the public health side and the transportation side are evaluated. We find that people's preventative behavior is one of the most effective measures to control the spreading of epidemics. From the transportation side, partial closure of bus routes helps to slow down but cannot fully contain the spreading of epidemics. Identifying "influential passengers" using the smart card data and isolating them at an early stage can also effectively reduce the epidemic spreading.
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Affiliation(s)
- Baichuan Mo
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Kairui Feng
- Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540, United States
| | - Yu Shen
- Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
| | - Clarence Tam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore
| | - Daqing Li
- School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
| | - Yafeng Yin
- Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48108, United States
| | - Jinhua Zhao
- Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
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22
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Elimian KO, Musah A, Ochu CL, Onwah SS, Oyebanji O, Yennan S, Fall IS, Yao M, Chukwuji M, Ekeng E, Abok P, Omar LH, Balde T, Kankia A, Williams N, Mutbam K, Dhamari N, Okudo I, Alemu W, Peter C, Ihekweazu C. Identifying and quantifying the factors associated with cholera-related death during the 2018 outbreak in Nigeria. Pan Afr Med J 2020; 37:368. [PMID: 33796181 PMCID: PMC7992435 DOI: 10.11604/pamj.2020.37.368.20981] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 02/19/2020] [Indexed: 11/11/2022] Open
Abstract
Introduction cholera outbreaks in Nigeria are often associated with high case fatality rates; however, there is a dearth of evidence on context-specific factors associated with the trend. This study therefore aimed to identify and quantify the factors associated with cholera-related deaths in Nigeria. Methods using a cross-sectional design, we analysed surveillance data from all the States that reported cholera cases during the 2018 outbreak, and defined cholera-related death as death of an individual classified as having cholera according to the Nigeria Centre for Disease Control case definition. Factors associated with cholera-related death were assessed using multivariable logistic regression and findings presented as adjusted odds ratios (ORs) with 95% Confidence Intervals (95% CIs). Results between January 1 and November 19, 2018, 41,394 cholera cases were reported across 20 States, including 815 cholera-related deaths. In the adjusted multivariable model, older age, male gender, living in peri-urban areas or in flooded states, infection during the rainy season, and delay in seeking health care by >2 days were positively associated with cholera-related death; whereas living in urban areas, hospitalisation in the course of illness, and presentation to a secondary hospital were negatively associated with cholera-related death. Conclusion cholera-related deaths during the 2018 outbreak in Nigeria appeared to be driven by multiple factors, which further reemphasises the importance of adopting a multisectoral approach to the design and implementation of context-specific interventions in Nigeria.
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Affiliation(s)
- Kelly Osezele Elimian
- Nigeria Centre for Disease Control, Abuja, Nigeria.,University of Benin, Edo State, Nigeria
| | - Anwar Musah
- University College London, London, United Kingdom
| | | | | | | | | | - Ibrahima Soce Fall
- World Health Organization/ Regional Office for Africa, Democratic Republic of Congo
| | - Michel Yao
- World Health Organization/ Regional Office for Africa, Democratic Republic of Congo
| | | | - Eme Ekeng
- Nigeria Centre for Disease Control, Abuja, Nigeria
| | - Patrick Abok
- World Health Organization/ Regional Office for Africa, Democratic Republic of Congo
| | - Linda Haj Omar
- World Health Organization/ Regional Office for Africa, Democratic Republic of Congo
| | - Thieno Balde
- World Health Organization/ Regional Office for Africa, Democratic Republic of Congo
| | - Adamu Kankia
- World Health Organization/ Regional Office for Africa, Democratic Republic of Congo
| | | | | | | | - Ifeanyi Okudo
- World Health Organization/ Regional Office for Africa, Democratic Republic of Congo
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Jones FK, Wamala JF, Rumunu J, Mawien PN, Kol MT, Wohl S, Deng L, Pezzoli L, Omar LH, Lessler J, Quilici ML, Luquero FJ, Azman AS. Successive epidemic waves of cholera in South Sudan between 2014 and 2017: a descriptive epidemiological study. Lancet Planet Health 2020; 4:e577-e587. [PMID: 33278375 PMCID: PMC7750463 DOI: 10.1016/s2542-5196(20)30255-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 10/15/2020] [Accepted: 10/16/2020] [Indexed: 05/16/2023]
Abstract
BACKGROUND Between 2014 and 2017, successive cholera epidemics occurred in South Sudan within the context of civil war, population displacement, flooding, and drought. We aim to describe the spatiotemporal and molecular features of the three distinct epidemic waves and explore the role of vaccination campaigns, precipitation, and population movement in shaping cholera spread in this complex setting. METHODS In this descriptive epidemiological study, we analysed cholera linelist data to describe the spatiotemporal progression of the epidemics. We placed whole-genome sequence data from pandemic Vibrio cholerae collected throughout these epidemics into the global phylogenetic context. Using whole-genome sequence data in combination with other molecular attributes, we characterise the relatedness of strains circulating in each wave and the region. We investigated the association of rainfall and the instantaneous basic reproduction number using distributed lag non-linear models, compared county-level attack rates between those with early and late reactive vaccination campaigns, and explored the consistency of the spatial patterns of displacement and suspected cholera case reports. FINDINGS The 2014 (6389 cases) and 2015 (1818 cases) cholera epidemics in South Sudan remained spatially limited whereas the 2016-17 epidemic (20 438 cases) spread among settlements along the Nile river. Initial cases of each epidemic were reported in or around Juba soon after the start of the rainy season, but we found no evidence that rainfall modulated transmission during each epidemic. All isolates analysed had similar genotypic and phenotypic characteristics, closely related to sequences from Uganda and Democratic Republic of the Congo. Large-scale population movements between counties of South Sudan with cholera outbreaks were consistent with the spatial distribution of cases. 21 of 26 vaccination campaigns occurred during or after the county-level epidemic peak. Counties vaccinated on or after the peak incidence week had 2·2 times (95% CI 2·1-2·3) higher attack rates than those where vaccination occurred before the peak. INTERPRETATION Pandemic V cholerae of the same clonal origin was isolated throughout the study period despite interepidemic periods of no reported cases. Although the complex emergency in South Sudan probably shaped some of the observed spatial and temporal patterns of cases, the full scope of transmission determinants remains unclear. Timely and well targeted use of vaccines can reduce the burden of cholera; however, rapid vaccine deployment in complex emergencies remains challenging. FUNDING The Bill & Melinda Gates Foundation.
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Affiliation(s)
- Forrest K Jones
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - John Rumunu
- Republic of South Sudan Ministry of Health, Juba, South Sudan
| | | | - Mathew Tut Kol
- Republic of South Sudan Ministry of Health, Juba, South Sudan
| | - Shirlee Wohl
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Lul Deng
- Republic of South Sudan Ministry of Health, Juba, South Sudan
| | | | - Linda Haj Omar
- World Health Organization, Brazzaville, Republic of Congo
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | - Andrew S Azman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Médecins Sans Frontières, Geneva, Switzerland.
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Sulyok M, Walker M. Community movement and COVID-19: a global study using Google's Community Mobility Reports. Epidemiol Infect 2020; 148:e284. [PMID: 33183366 PMCID: PMC7729173 DOI: 10.1017/s0950268820002757] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 09/25/2020] [Accepted: 11/06/2020] [Indexed: 11/25/2022] Open
Abstract
Google's 'Community Mobility Reports' (CMR) detail changes in activity and mobility occurring in response to COVID-19. They thus offer the unique opportunity to examine the relationship between mobility and disease incidence. The objective was to examine whether an association between COVID-19-confirmed case numbers and levels of mobility was apparent, and if so then to examine whether such data enhance disease modelling and prediction. CMR data for countries worldwide were cross-correlated with corresponding COVID-19-confirmed case numbers. Models were fitted to explain case numbers of each country's epidemic. Models using numerical date, contemporaneous and distributed lag CMR data were contrasted using Bayesian Information Criteria. Noticeable were negative correlations between CMR data and case incidence for prominent industrialised countries of Western Europe and the North Americas. Continent-wide examination found a negative correlation for all continents with the exception of South America. When modelling, CMR-expanded models proved superior to the model without CMR. The predictions made with the distributed lag model significantly outperformed all other models. The observed relationship between CMR data and case incidence, and its ability to enhance model quality and prediction suggests data related to community mobility could prove of use in future COVID-19 modelling.
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Affiliation(s)
- M. Sulyok
- Institute of Tropical Medicine, Eberhard Karls University, University Clinics Tübingen, Wilhelmstr. 27, 72074, Tübingen, Germany
- Department of Pathology, Institute of Pathology and Neuropathology, Eberhard Karls University, University Clinics Tübingen, Liebermeisterstr. 8, 72076, Tübingen, Germany
| | - M. Walker
- Department of the Natural and Built Environment, Sheffield Hallam University, Howard Street, S1 1WB, Sheffield, UK
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25
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Kinsley AC, Rossi G, Silk MJ, VanderWaal K. Multilayer and Multiplex Networks: An Introduction to Their Use in Veterinary Epidemiology. Front Vet Sci 2020; 7:596. [PMID: 33088828 PMCID: PMC7500177 DOI: 10.3389/fvets.2020.00596] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 07/27/2020] [Indexed: 11/13/2022] Open
Abstract
Contact network analysis has become a vital tool for conceptualizing the spread of pathogens in animal populations and is particularly useful for understanding the implications of heterogeneity in contact patterns for transmission. However, the transmission of most pathogens cannot be simplified to a single mode of transmission and, thus, a single definition of contact. In addition, host-pathogen interactions occur in a community context, with many pathogens infecting multiple host species and most hosts being infected by multiple pathogens. Multilayer networks provide a formal framework for researching host-pathogen systems in which multiple types of transmission-relevant interactions, defined as network layers, can be analyzed jointly. Here, we provide an overview of multilayer network analysis and review applications of this novel method to epidemiological research questions. We then demonstrate the use of this technique to analyze heterogeneity in direct and indirect contact patterns amongst swine farms in the United States. When contact among nodes can be defined in multiple ways, a multilayer approach can advance our ability to use networks in epidemiological research by providing an improved approach for defining epidemiologically relevant groups of interacting nodes and changing the way we identify epidemiologically important individuals such as superspreaders.
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Affiliation(s)
- Amy C Kinsley
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States
| | - Gianluigi Rossi
- Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthew J Silk
- Centre for Ecology and Conservation, University of Exeter Penryn Campus, Penryn, United Kingdom.,Environment and Sustainability Institute, University of Exeter, Penryn, United Kingdom
| | - Kimberly VanderWaal
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States
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26
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Fitzgibbon WE, Morgan JJ, Webb GF, Wu Y. Modelling the aqueous transport of an infectious pathogen in regional communities: application to the cholera outbreak in Haiti. J R Soc Interface 2020; 17:20200429. [PMID: 32752993 DOI: 10.1098/rsif.2020.0429] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A mathematical model is developed to describe the dynamics of the spread of a waterborne disease among communities located along a flowing waterway. The model is formulated as a system of reaction-diffusion-advection partial differential equations in this spatial setting. The compartments of the model consist of susceptible, infected, and recovered individuals in the communities along the waterway, together with a term representing the pathogen load in each community and a term representing the spatial concentration of pathogens flowing along the waterway. The model is applied to the cholera outbreak in Haiti in 2010.
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Affiliation(s)
| | - Jeffrey J Morgan
- Department of Mathematics, University of Houston, Houston, TX 77204, USA
| | - Glenn F Webb
- Department of Mathematics, Vanderbilt University, Nashville, TN 37212, USA
| | - Yixiang Wu
- Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, TN 37132, USA
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27
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Smirnova A, Sterrett N, Mujica OJ, Munayco C, Suárez L, Viboud C, Chowell G. Spatial dynamics and the basic reproduction number of the 1991-1997 Cholera epidemic in Peru. PLoS Negl Trop Dis 2020; 14:e0008045. [PMID: 32663235 PMCID: PMC7360044 DOI: 10.1371/journal.pntd.0008045] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 01/09/2020] [Indexed: 11/18/2022] Open
Abstract
After being cholera free for over 100 years, Peru experienced an unprecedented epidemic of Vibrio cholerae O1 that began in 1991 and generated multiple waves of disease over several years. We developed a mechanistic transmission model that accounts for seasonal variation in temperature to estimate spatial variability in the basic reproduction number ([Formula: see text]), the initial concentration of vibrios in the environment, and cholera reporting rates. From 1991-1997, cholera spread following a multi-wave pattern, with weekly incidence concentrated during warm seasons. The epidemic first hit the coastal departments of Peru and subsequently spread through the highlands and jungle regions. The correlation between model predictions and observations was high (range in R2: 58% to 97%). Department-level population size and elevation explained significant variation in spatial-temporal transmission patterns. The overall R0 across departments was estimated at 2.1 (95% CI: 0.8,7.3), high enough for sustained transmission. Geographic-region level [Formula: see text] varied substantially from 2.4 (95% CI: 1.1, 7.3) for the coastal region, 1.9 (0.7, 6.4) for the jungle region, and 1.5 (0.9, 2.2) for the highlands region. At the department level, mean [Formula: see text] ranged from 0.8 to 6.9. Department-level [Formula: see text] were correlated with overall observed attack rates (Spearman ρ = 0.59, P = 0.002), elevation (ρ = -0.4, P = 0.04), and longitude (ρ = -0.6, P = 0.004). We find that both [Formula: see text] and the initial concentration of vibrios were higher in coastal departments than other departments. Reporting rates were low, consistent with a substantial fraction of asymptomatic or mild cases associated with the El Tor cholera biotype. Our results suggest that cholera vibrios, autochthonous to plankton in the natural aquatic environment, may have triggered outbreaks in multiple coastal locations along the Pacific coast of Peru. Our methodology could be useful to investigate multi-wave epidemics of cholera and could be extended to conduct near real-time forecasts and investigate the impact of vaccination strategies.
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Affiliation(s)
- Alexandra Smirnova
- Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia, United States of America
| | - Natalie Sterrett
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America
| | - Oscar J. Mujica
- Pan American Health Organization (PAHO), Washington DC, United States of America
| | - César Munayco
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Lima, Peru
| | - Luis Suárez
- Centro Nacional de Epidemiología, Prevención y Control de Enfermedades, Lima, Peru
| | - Cécile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Gerardo Chowell
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
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Meszaros VA, Miller-Dickson MD, Baffour-Awuah F, Almagro-Moreno S, Ogbunugafor CB. Direct transmission via households informs models of disease and intervention dynamics in cholera. PLoS One 2020; 15:e0229837. [PMID: 32163436 PMCID: PMC7067450 DOI: 10.1371/journal.pone.0229837] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 02/14/2020] [Indexed: 02/07/2023] Open
Abstract
While several basic properties of cholera outbreaks are common to most settings-the pathophysiology of the disease, the waterborne nature of transmission, and others-recent findings suggest that transmission within households may play a larger role in cholera outbreaks than previously appreciated. Important features of cholera outbreaks have long been effectively modeled with mathematical and computational approaches, but little is known about how variation in direct transmission via households may influence epidemic dynamics. In this study, we construct a mathematical model of cholera that incorporates transmission within and between households. We observe that variation in the magnitude of household transmission changes multiple features of disease dynamics, including the severity and duration of outbreaks. Strikingly, we observe that household transmission influences the effectiveness of possible public health interventions (e.g. water treatment, antibiotics, vaccines). We find that vaccine interventions are more effective than water treatment or antibiotic administration when direct household transmission is present. Summarizing, we position these results within the landscape of existing models of cholera, and speculate on its implications for epidemiology and public health.
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Affiliation(s)
- Victor A. Meszaros
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, United States of America
| | - Miles D. Miller-Dickson
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, United States of America
| | - Francis Baffour-Awuah
- Department of Mathematics, Florida State University, Tallahassee, FL, United States of America
| | - Salvador Almagro-Moreno
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, United States of America
- National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL, United States of America
| | - C. Brandon Ogbunugafor
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, United States of America
- * E-mail:
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LUPICA ANTONELLA, GUMEL ABBAB, PALUMBO ANNUNZIATA. THE COMPUTATION OF REPRODUCTION NUMBERS FOR THE ENVIRONMENT-HOST-ENVIRONMENT CHOLERA TRANSMISSION DYNAMICS. J BIOL SYST 2020. [DOI: 10.1142/s021833902040001x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
This study presents a new model for the environment-host-environment transmission dynamics of V. cholerae in a community with an interconnected aquatic pond–river water network. For the case when the human host is the sole target of anti-cholera control and the volume of water in the pond is maximum, the disease-free equilibrium of the model is shown to be globally asymptotically stable whenever a certain epidemiological threshold, known as the basic reproduction number [Formula: see text], is less than unity. The epidemiological implication of this result is that cholera can be eliminated from the community if the control strategies implemented can bring (and maintain) [Formula: see text] to a value less than unity. Four scenarios, that represent different interpretations of the role of the V. cholerea pathogen within the environment, were studied. The corresponding basic reproduction numbers were shown to exhibit the same threshold property with respect to the value unity (i.e., if one is less (equal, greater) than unity, then the three others are also less (equal, greater) than unity. Further, it was shown that for the case where anti-cholera control is focused on the human host population, the associated type reproduction number of the model (corresponding to each of the four transmission scenarios considered) is unique. The implication of this result is that the estimate of the effort needed for disease elimination (i.e., the required herd immunity threshold) is unique, regardless of which of the four transmission scenarios is considered. However, when any of the other two bacterial population types in the aquatic environment (i.e., bacterial in the pond or river) is the focus of the control efforts, this study shows that the associated type reproduction number is not unique. Extensive numerical simulations of the model, using a realistic set of parameters from the published literature, show that the community-wide implementation of a strategy that focus on improved water quality, sanitation, and hygiene (known as WASH-only strategy), using the current estimated coverage of 50% and efficacy of 60%, is unable to lead to the elimination of the disease. Such elimination is attainable if the coverage and efficacy are increased (e.g., to 80% and 90%, respectively). Further, elimination can be achieved using a strategy that focuses on oral rehydration therapy and the use of antibiotics to treat the infected humans (i.e., treatment-only strategy) for moderate effectiveness and coverage levels. The combined hybrid WASH-treatment strategy provides far better population-level impact vis a vis disease elimination. This study ranks the three interventions in the following order of population-level effectiveness: combined WASH-treatment, followed by treatment-only and then WASH-only strategy.
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Affiliation(s)
- ANTONELLA LUPICA
- Department of Mathematics and Computer Sciences, University of Catania, V.le A. Doria 6, 95125 Catania, Italy
- Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences, University of Messina, V.le F. D’Alcontres 31, 98166 Messina, Italy
| | - ABBA B. GUMEL
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona, USA
- Department of Mathematics and Applied Mathematics, University of Pretoria, Pretoria 0002, South Africa
| | - ANNUNZIATA PALUMBO
- Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences, University of Messina, V.le F. D’Alcontres 31, 98166 Messina, Italy
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Lanzas C, Davies K, Erwin S, Dawson D. On modelling environmentally transmitted pathogens. Interface Focus 2020; 10:20190056. [PMID: 31897293 PMCID: PMC6936006 DOI: 10.1098/rsfs.2019.0056] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/01/2019] [Indexed: 12/11/2022] Open
Abstract
Many pathogens are able to replicate or survive in abiotic environments. Disease transmission models that include environmental reservoirs and environment-to-host transmission have used a variety of functional forms and modelling frameworks without a clear connection to pathogen ecology or space and time scales. We present a conceptual framework to organize microparasites based on the role that abiotic environments play in their lifecycle. Mean-field and individual-based models for environmental transmission are analysed and compared. We show considerable divergence between both modelling approaches when conditions do not facilitate well mixing and for pathogens with fast dynamics in the environment. We conclude with recommendations for modelling environmentally transmitted pathogens based on the pathogen lifecycle and time and spatial scales of the host-pathogen system under consideration.
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Affiliation(s)
- Cristina Lanzas
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC, USA
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Abd El Ghany M, Fouz N, Hill-Cawthorne GA. Human Movement and Transmission of Antimicrobial-Resistant Bacteria. THE HANDBOOK OF ENVIRONMENTAL CHEMISTRY 2020:311-344. [DOI: 10.1007/698_2020_560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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Phelps MD, Simonsen L, Jensen PKM. Individual and household exposures associated with cholera transmission in case–control studies: a systematic review. Trop Med Int Health 2019; 24:1151-1168. [DOI: 10.1111/tmi.13293] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Matthew D. Phelps
- Copenhagen Center for Disaster Research, Department of Public Health, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
| | - Lone Simonsen
- Department of Science and Environment Roskilde University Roskilde Denmark
| | - Peter K. M. Jensen
- Copenhagen Center for Disaster Research, Department of Public Health, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
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Brouwer AF, Masters NB, Eisenberg JNS. Quantitative Microbial Risk Assessment and Infectious Disease Transmission Modeling of Waterborne Enteric Pathogens. Curr Environ Health Rep 2019; 5:293-304. [PMID: 29679300 DOI: 10.1007/s40572-018-0196-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
PURPOSE OF REVIEW Waterborne enteric pathogens remain a global health threat. Increasingly, quantitative microbial risk assessment (QMRA) and infectious disease transmission modeling (IDTM) are used to assess waterborne pathogen risks and evaluate mitigation. These modeling efforts, however, have largely been conducted independently for different purposes and in different settings. In this review, we examine the settings where each modeling strategy is employed. RECENT FINDINGS QMRA research has focused on food contamination and recreational water in high-income countries (HICs) and drinking water and wastewater in low- and middle-income countries (LMICs). IDTM research has focused on large outbreaks (predominately LMICs) and vaccine-preventable diseases (LMICs and HICs). Human ecology determines the niches that pathogens exploit, leading researchers to focus on different risk assessment research strategies in different settings. To enhance risk modeling, QMRA and IDTM approaches should be integrated to include dynamics of pathogens in the environment and pathogen transmission through populations.
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Affiliation(s)
- Andrew F Brouwer
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Nina B Masters
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
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Mari L, Casagrandi R, Bertuzzo E, Rinaldo A, Gatto M. Conditions for transient epidemics of waterborne disease in spatially explicit systems. ROYAL SOCIETY OPEN SCIENCE 2019; 6:181517. [PMID: 31218018 PMCID: PMC6549988 DOI: 10.1098/rsos.181517] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 03/12/2019] [Indexed: 05/06/2023]
Abstract
Waterborne diseases are a diverse family of infections transmitted through ingestion of-or contact with-water infested with pathogens. Outbreaks of waterborne infections often show well-defined spatial signatures that are typically linked to local eco-epidemiological conditions, water-mediated pathogen transport and human mobility. In this work, we apply a spatially explicit network model describing the transmission cycle of waterborne pathogens to determine invasion conditions in metacommunities endowed with a realistic spatial structure. Specifically, we aim to define conditions under which pathogens can temporarily colonize a set of human communities, thus triggering a transient epidemic outbreak. To that end, we apply generalized reactivity analysis, a recently developed methodological framework for the study of transient dynamics in ecological systems subject to external perturbations. The study of pathogen invasion is complemented by the detection of the spatial signatures associated with the perturbations to a disease-free system that are expected to be amplified the most over different time scales. Understanding the drivers of waterborne disease dynamics over time scales that are relevant to epidemic and/or endemic transmission is a crucial, cross-disciplinary challenge, as large portions of the developing world still struggle to cope with the burden of these infections.
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Affiliation(s)
- Lorenzo Mari
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy
- Author for correspondence: Lorenzo Mari e-mail:
| | - Renato Casagrandi
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy
| | - Enrico Bertuzzo
- Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca’ Foscari Venezia, 30170 Venezia Mestre, Italy
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
- Dipartimento ICEA, Università di Padova, 35131 Padova, Italy
| | - Marino Gatto
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy
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Phelps M, Perner ML, Pitzer VE, Andreasen V, Jensen PKM, Simonsen L. Cholera Epidemics of the Past Offer New Insights Into an Old Enemy. J Infect Dis 2019; 217:641-649. [PMID: 29165706 PMCID: PMC5853221 DOI: 10.1093/infdis/jix602] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 11/16/2017] [Indexed: 11/20/2022] Open
Abstract
Background Although cholera is considered the quintessential long-cycle waterborne disease, studies have emphasized the existence of short-cycle (food, household) transmission. We investigated singular Danish cholera epidemics (in 1853) to elucidate epidemiological parameters and modes of spread. Methods Using time series data from cities with different water systems, we estimated the intrinsic transmissibility (R0). Accessing cause-specific mortality data, we studied clinical severity and age-specific impact. From physicians’ narratives we established transmission chains and estimated serial intervals. Results Epidemics were seeded by travelers from cholera-affected cities; initial transmission chains involving household members and caretakers ensued. Cholera killed 3.4%–8.9% of the populations, with highest mortality among seniors (16%) and lowest in children (2.7%). Transmissibility (R0) was 1.7–2.6 and the serial interval was estimated at 3.7 days (95% confidence interval, 2.9–4.7 days). The case fatality ratio (CFR) was high (54%–68%); using R0 we computed an adjusted CFR of 4%–5%. Conclusions Short-cycle transmission was likely critical to early secondary transmission in historic Danish towns. The outbreaks resembled the contemporary Haiti outbreak with respect to transmissibility, age patterns, and CFR, suggesting a role for broader hygiene/sanitation interventions to control contemporary outbreaks.
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Affiliation(s)
- Matthew Phelps
- Copenhagen Center for Disaster Research, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Mads Linnet Perner
- Copenhagen Center for Disaster Research, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut
| | - Viggo Andreasen
- Department of Science and the Environment, Roskilde University, Denmark
| | - Peter K M Jensen
- Copenhagen Center for Disaster Research, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Lone Simonsen
- Copenhagen Center for Disaster Research, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.,Department of Science and the Environment, Roskilde University, Denmark
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Mapping Multi-Disease Risk during El Niño: An Ecosyndemic Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15122639. [PMID: 30477272 PMCID: PMC6313459 DOI: 10.3390/ijerph15122639] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 11/04/2018] [Accepted: 11/21/2018] [Indexed: 01/10/2023]
Abstract
El Niño is a quasi-periodic pattern of climate variability and extremes often associated with hazards and disease. While El Niño links to individual diseases have been examined, less is known about the cluster of multi-disease risk referred to as an ecosyndemic, which emerges during extreme events. The objective of this study was to explore a mapping approach to represent the spatial distribution of ecosyndemics in Piura, Peru at the district-level during the first few months of 1998. Using geographic information systems and multivariate analysis, descriptive and analytical methodologies were employed to map disease overlap of 7 climate-sensitive diseases and construct an ecosyndemic index, which was then mapped and applied to another El Niño period as proof of concept. The main findings showed that many districts across Piura faced multi-disease risk over several weeks in the austral summer of 1998. The distribution of ecosyndemics were spatially clustered in western Piura among 11 districts. Furthermore, the ecosydemic index in 1998 when compared to 1983 showed a strong positive correlation, demonstrating the potential utility of the index. The study supports PAHO efforts to develop multi-disease based and interprogrammatic approaches to control and prevention, particularly for climate and poverty-related infections in Latin America and the Caribbean.
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Pasetto D, Finger F, Camacho A, Grandesso F, Cohuet S, Lemaitre JC, Azman AS, Luquero FJ, Bertuzzo E, Rinaldo A. Near real-time forecasting for cholera decision making in Haiti after Hurricane Matthew. PLoS Comput Biol 2018; 14:e1006127. [PMID: 29768401 PMCID: PMC5973636 DOI: 10.1371/journal.pcbi.1006127] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 05/29/2018] [Accepted: 04/09/2018] [Indexed: 12/04/2022] Open
Abstract
Computational models of cholera transmission can provide objective insights into the course of an ongoing epidemic and aid decision making on allocation of health care resources. However, models are typically designed, calibrated and interpreted post-hoc. Here, we report the efforts of a team from academia, field research and humanitarian organizations to model in near real-time the Haitian cholera outbreak after Hurricane Matthew in October 2016, to assess risk and to quantitatively estimate the efficacy of a then ongoing vaccination campaign. A rainfall-driven, spatially-explicit meta-community model of cholera transmission was coupled to a data assimilation scheme for computing short-term projections of the epidemic in near real-time. The model was used to forecast cholera incidence for the months after the passage of the hurricane (October-December 2016) and to predict the impact of a planned oral cholera vaccination campaign. Our first projection, from October 29 to December 31, predicted the highest incidence in the departments of Grande Anse and Sud, accounting for about 45% of the total cases in Haiti. The projection included a second peak in cholera incidence in early December largely driven by heavy rainfall forecasts, confirming the urgency for rapid intervention. A second projection (from November 12 to December 31) used updated rainfall forecasts to estimate that 835 cases would be averted by vaccinations in Grande Anse (90% Prediction Interval [PI] 476-1284) and 995 in Sud (90% PI 508-2043). The experience gained by this modeling effort shows that state-of-the-art computational modeling and data-assimilation methods can produce informative near real-time projections of cholera incidence. Collaboration among modelers and field epidemiologists is indispensable to gain fast access to field data and to translate model results into operational recommendations for emergency management during an outbreak. Future efforts should thus draw together multi-disciplinary teams to ensure model outputs are appropriately based, interpreted and communicated.
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Affiliation(s)
- Damiano Pasetto
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Flavio Finger
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Anton Camacho
- Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Epicentre, Paris, France
| | | | | | - Joseph C. Lemaitre
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Andrew S. Azman
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Francisco J. Luquero
- Epicentre, Geneva, Switzerland
- Department of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Enrico Bertuzzo
- Department of Environmental Sciences, Informatics and Statistics, University Ca’ Foscari Venezia, Venezia Mestre, Italy
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Civil, Environmental and Architectural Engineering, University of Padua, Padova, Italy
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Mari L, Casagrandi R, Rinaldo A, Gatto M. Epidemicity thresholds for water-borne and water-related diseases. J Theor Biol 2018; 447:126-138. [PMID: 29588168 DOI: 10.1016/j.jtbi.2018.03.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Revised: 02/02/2018] [Accepted: 03/16/2018] [Indexed: 12/18/2022]
Abstract
Determining the conditions that favor pathogen establishment in a host community is key to disease control and eradication. However, focusing on long-term dynamics alone may lead to an underestimation of the threats imposed by outbreaks triggered by short-term transient phenomena. Achieving an effective epidemiological response thus requires to look at different timescales, each of which may be endowed with specific management objectives. In this work we aim to determine epidemicity thresholds for some prototypical examples of water-borne and water-related diseases, a diverse family of infections transmitted either directly through water infested with pathogens or by vectors whose lifecycles are closely associated with water. From a technical perspective, while conditions for endemicity are determined via stability analysis, epidemicity thresholds are defined through generalized reactivity analysis, a recently proposed method that allows the study of the short-term instability properties of ecological systems. Understanding the drivers of water-borne and water-related disease dynamics over timescales that may be relevant to epidemic and/or endemic transmission is a challenge of the utmost importance, as large portions of the developing world are still struggling with the burden imposed by these infections.
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Affiliation(s)
- Lorenzo Mari
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy.
| | - Renato Casagrandi
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland; Dipartimento ICEA, Università di Padova, Padova 35131, Italy
| | - Marino Gatto
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano 20133, Italy
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Rinaldo A, Gatto M, Rodriguez-Iturbe I. River networks as ecological corridors: A coherent ecohydrological perspective. ADVANCES IN WATER RESOURCES 2018; 112:27-58. [PMID: 29651194 PMCID: PMC5890385 DOI: 10.1016/j.advwatres.2017.10.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 10/05/2017] [Accepted: 10/06/2017] [Indexed: 05/14/2023]
Abstract
This paper draws together several lines of argument to suggest that an ecohydrological framework, i.e. laboratory, field and theoretical approaches focused on hydrologic controls on biota, has contributed substantially to our understanding of the function of river networks as ecological corridors. Such function proves relevant to: the spatial ecology of species; population dynamics and biological invasions; the spread of waterborne disease. As examples, we describe metacommunity predictions of fish diversity patterns in the Mississippi-Missouri basin, geomorphic controls imposed by the fluvial landscape on elevational gradients of species' richness, the zebra mussel invasion of the same Mississippi-Missouri river system, and the spread of proliferative kidney disease in salmonid fish. We conclude that spatial descriptions of ecological processes in the fluvial landscape, constrained by their specific hydrologic and ecological dynamics and by the ecosystem matrix for interactions, i.e. the directional dispersal embedded in fluvial and host/pathogen mobility networks, have already produced a remarkably broad range of significant results. Notable scientific and practical perspectives are thus open, in the authors' view, to future developments in ecohydrologic research.
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Affiliation(s)
- Andrea Rinaldo
- Laboratory of Ecohydrology ECHO/IIE/ENAC, École Polytechinque Fédérale de Lausanne, Lausanne, CH, Switzerland
- Dipartimento ICEA, Università di Padova, Padova, IT, Italy
| | - Marino Gatto
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano IT, Italy
| | - Ignacio Rodriguez-Iturbe
- Department of Ocean Engineering, Department of Civil Engineering and Department of Biological and Agricultural Engineering, Texas A & M University, College Station (TX), USA
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Perez-Saez J, King AA, Rinaldo A, Yunus M, Faruque ASG, Pascual M. Climate-driven endemic cholera is modulated by human mobility in a megacity. ADVANCES IN WATER RESOURCES 2017; 108:367-376. [PMID: 29081572 PMCID: PMC5654324 DOI: 10.1016/j.advwatres.2016.11.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Although a differential sensitivity of cholera dynamics to climate variability has been reported in the spatially heterogeneous megacity of Dhaka, Bangladesh, the specific patterns of spread of the resulting risk within the city remain unclear. We build on an established probabilistic spatial model to investigate the importance and role of human mobility in modulating spatial cholera transmission. Mobility fluxes were inferred using a straightforward and generalizable methodology that relies on mapping population density based on a high resolution urban footprint product, and a parameter-free human mobility model. In accordance with previous findings, we highlight the higher sensitivity to the El Niño Southern Oscillation (ENSO) in the highly populated urban center than in the more rural periphery. More significantly, our results show that cholera risk is largely transmitted from the climate-sensitive core to the periphery of the city, with implications for the planning of control efforts. In addition, including human mobility improves the outbreak prediction performance of the model with an 11 month lead. The interplay between climatic and human mobility factors in cholera transmission is discussed from the perspective of the rapid growth of megacities across the developing world.
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Affiliation(s)
- Javier Perez-Saez
- Laboratory of Ecohydrology, Ecole Polytechnique Fédérale de Lausanne, CH-1015, Switzerland
| | - Aaron A King
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, Ecole Polytechnique Fédérale de Lausanne, CH-1015, Switzerland
| | - Mohammad Yunus
- International Centre for Diarrheal Disease Research, Dhaka 1000, Bangladesh
| | - Abu S G Faruque
- International Centre for Diarrheal Disease Research, Dhaka 1000, Bangladesh
| | - Mercedes Pascual
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA
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41
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Wesolowski A, Buckee CO, Engø-Monsen K, Metcalf CJE. Connecting Mobility to Infectious Diseases: The Promise and Limits of Mobile Phone Data. J Infect Dis 2017; 214:S414-S420. [PMID: 28830104 DOI: 10.1093/infdis/jiw273] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Human travel can shape infectious disease dynamics by introducing pathogens into susceptible populations or by changing the frequency of contacts between infected and susceptible individuals. Quantifying infectious disease-relevant travel patterns on fine spatial and temporal scales has historically been limited by data availability. The recent emergence of mobile phone calling data and associated locational information means that we can now trace fine scale movement across large numbers of individuals. However, these data necessarily reflect a biased sample of individuals across communities and are generally aggregated for both ethical and pragmatic reasons that may further obscure the nuance of individual and spatial heterogeneities. Additionally, as a general rule, the mobile phone data are not linked to demographic or social identifiers, or to information about the disease status of individual subscribers (although these may be made available in smaller-scale specific cases). Combining data on human movement from mobile phone data-derived population fluxes with data on disease incidence requires approaches that can tackle varying spatial and temporal resolutions of each data source and generate inference about dynamics on scales relevant to both pathogen biology and human ecology. Here, we review the opportunities and challenges of these novel data streams, illustrating our examples with analyses of 2 different pathogens in Kenya, and conclude by outlining core directions for future research.
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Affiliation(s)
- Amy Wesolowski
- Department of Epidemiology.,Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Caroline O Buckee
- Department of Epidemiology.,Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | | | - C J E Metcalf
- Department of Ecology and Evolutionary Biology.,Office of Population Research, Woodrow Wilson School, Princeton University, New Jersey
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42
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Mari L, Ciddio M, Casagrandi R, Perez-Saez J, Bertuzzo E, Rinaldo A, Sokolow SH, De Leo GA, Gatto M. Heterogeneity in schistosomiasis transmission dynamics. J Theor Biol 2017; 432:87-99. [PMID: 28823529 PMCID: PMC5595357 DOI: 10.1016/j.jtbi.2017.08.015] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 06/30/2017] [Accepted: 08/15/2017] [Indexed: 01/30/2023]
Abstract
Transmission dynamics of schistosomiasis presents multiple heterogeneity sources. A comprehensive framework for heterogeneous disease transmission is proposed. Heterogeneous multigroup communities can be more prone to parasite transmission. Presence of multiple water sources can hinder parasite transmission. Spatial and temporal heterogeneities can have nontrivial implications for endemicity.
Simple models of disease propagation often disregard the effects of transmission heterogeneity on the ecological and epidemiological dynamics associated with host-parasite interactions. However, for some diseases like schistosomiasis, a widespread parasitic infection caused by Schistosoma worms, accounting for heterogeneity is crucial to both characterize long-term dynamics and evaluate opportunities for disease control. Elaborating on the classic Macdonald model for macroparasite transmission, we analyze families of models including explicit descriptions of heterogeneity related to differential transmission risk within a community, water contact patterns, the distribution of the snail host population, human mobility, and the seasonal fluctuations of the environment. Through simple numerical examples, we show that heterogeneous multigroup communities may be more prone to schistosomiasis than homogeneous ones, that the availability of multiple water sources can hinder parasite transmission, and that both spatial and temporal heterogeneities may have nontrivial implications for disease endemicity. Finally, we discuss the implications of heterogeneity for disease control. Although focused on schistosomiasis, results from this study may apply as well to other parasitic infections with complex transmission cycles, such as cysticercosis, dracunculiasis and fasciolosis.
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Affiliation(s)
- Lorenzo Mari
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
| | - Manuela Ciddio
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy
| | - Renato Casagrandi
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy
| | - Javier Perez-Saez
- Laboratory of Ecohydrology, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Enrico Bertuzzo
- Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca' Foscari Venezia, 30170 Venezia Mestre, Italy
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland; Dipartimento ICEA, Università di Padova, 35131 Padova, Italy
| | - Susanne H Sokolow
- Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA; Marine Science Institute, University of California, Santa Barbara, CA 93106, USA
| | - Giulio A De Leo
- Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA
| | - Marino Gatto
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy
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43
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Mononen T, Ruokolainen L. Spatial disease dynamics of free-living pathogens under pathogen predation. Sci Rep 2017; 7:7729. [PMID: 28798313 PMCID: PMC5552698 DOI: 10.1038/s41598-017-07983-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 07/03/2017] [Indexed: 11/09/2022] Open
Abstract
The epidemiological dynamics of potentially free-living pathogens are often studied with respect to a specific pathogen species (e.g., cholera) and most studies concentrate only on host-pathogen interactions. Here we show that metacommunity-level interactions can alter conventional spatial disease dynamics. We introduce a pathogen eating consumer species and investigate a deterministic epidemiological model of two habitat patches, where both patches can be occupied by hosts, pathogens, and consumers of free-living pathogens. An isolated habitat patch shows periodic disease outbreaks in the host population, arising from cyclic consumer-pathogen dynamics. On the other hand, consumer dispersal between the patches generate asymmetric disease prevalence, such that the host population in one patch stays disease-free, while disease outbreaks occur in the other patch. Such asymmetry can also arise with host dispersal, where infected hosts carry pathogens to the other patch. This indirect movement of pathogens causes also a counter-intuitive effect: decreasing morbidity in a focal patch under increasing pathogen immigration. Our results underline that community-level interactions influence disease dynamics and consistent spatial asymmetry can arise also in spatially homogeneous systems.
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Affiliation(s)
- Tommi Mononen
- University of Helsinki, Department of Biosciences, Helsinki, FI-00014, Finland.
| | - Lasse Ruokolainen
- University of Helsinki, Department of Biosciences, Helsinki, FI-00014, Finland
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44
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Matias WR, Teng JE, Hilaire IJ, Harris JB, Franke MF, Ivers LC. Household and Individual Risk Factors for Cholera among Cholera Vaccine Recipients in Rural Haiti. Am J Trop Med Hyg 2017; 97:436-442. [PMID: 28722575 PMCID: PMC5544067 DOI: 10.4269/ajtmh.16-0407] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Oral cholera vaccination was used as part of cholera control in Haiti, but the vaccine does not provide complete protection. We conducted secondary data analyses of a vaccine effectiveness study in Haiti to evaluate risk factors for cholera among cholera vaccine recipients. Individuals vaccinated against cholera that presented with acute watery diarrhea and had a stool sample positive for Vibrio cholerae O1 were included as cases. Up to four vaccinated individuals who did not present for treatment of diarrhea were included as controls for each case, and matched by location of residence, enrollment time, and age. We evaluated sociodemographic characteristics and risk factors for cholera. Univariable and multivariable logistic regression were performed to identify risk factors for cholera among vaccinees. Thirty-three vaccine recipients with culture-confirmed cholera were included as cases. One-hundred-and-seventeen of their matched controls reported receiving vaccine and were included as controls. In a multivariable analysis, self-reporting use of branded household water disinfection products as a means of treating water (adjusted relative risk [aRR] = 44.3, 95% confidence interval [CI] = 4.19-468.05, P = 0.002), and reporting having a latrine as the main household toilet (aRR = 4.22, 95% CI = 1.23-14.43, P = 0.02), were independent risk factors for cholera. Self-reporting always treating water (aRR = 0.09, 95% CI = 0.01-0.57, P = 0.01) was associated with protection against cholera. The field effectiveness of water, sanitation, and hygiene interventions used in combination with cholera vaccination in cholera control should be measured and monitored over time to identify and remediate shortcomings, and ensure successful impact on disease control.
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Affiliation(s)
- Wilfredo R Matias
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts.,Partners In Health, Boston, Massachusetts
| | - Jessica E Teng
- Partners In Health, Boston, Massachusetts.,Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts
| | | | - Jason B Harris
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts
| | - Molly F Franke
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts
| | - Louise C Ivers
- Partners In Health, Boston, Massachusetts.,Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts.,Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts
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45
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Lo Iacono G, Armstrong B, Fleming LE, Elson R, Kovats S, Vardoulakis S, Nichols GL. Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review. PLoS Negl Trop Dis 2017; 11:e0005659. [PMID: 28604791 PMCID: PMC5481148 DOI: 10.1371/journal.pntd.0005659] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 06/22/2017] [Accepted: 05/23/2017] [Indexed: 11/19/2022] Open
Abstract
Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally.
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Affiliation(s)
- Giovanni Lo Iacono
- Chemical and Environmental Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, United Kingdom
| | - Ben Armstrong
- Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Lora E. Fleming
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, Cornwall, United Kingdom
| | - Richard Elson
- Gastrointestinal Infections, National Infection Service, Public Health England, London, United Kingdom
| | - Sari Kovats
- Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Sotiris Vardoulakis
- Chemical and Environmental Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, United Kingdom
- Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, London, United Kingdom
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, Cornwall, United Kingdom
- Institute of Occupational Medicine, Edinburgh, United Kingdom
| | - Gordon L. Nichols
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, Cornwall, United Kingdom
- Gastrointestinal Infections, National Infection Service, Public Health England, London, United Kingdom
- University of East Anglia, Norwich, United Kingdom
- University of Thessaly, Larissa, Thessaly, Greece
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46
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Rinaldo A, Bertuzzo E, Blokesch M, Mari L, Gatto M. Modeling Key Drivers of Cholera Transmission Dynamics Provides New Perspectives for Parasitology. Trends Parasitol 2017; 33:587-599. [PMID: 28483382 DOI: 10.1016/j.pt.2017.04.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Revised: 04/01/2017] [Accepted: 04/10/2017] [Indexed: 11/15/2022]
Abstract
Hydroclimatological and anthropogenic factors are key drivers of waterborne disease transmission. Information on human settlements and host mobility on waterways along which pathogens and hosts disperse, and relevant hydroclimatological processes, can be acquired remotely and included in spatially explicit mathematical models of disease transmission. In the case of epidemic cholera, such models allowed the description of complex disease patterns and provided insight into the course of ongoing epidemics. The inclusion of spatial information in models of disease transmission can aid in emergency management and the assessment of alternative interventions. Here, we review the study of drivers of transmission via spatially explicit approaches and argue that, because many parasitic waterborne diseases share the same drivers as cholera, similar principles may apply.
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Affiliation(s)
- Andrea Rinaldo
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Dipartimento ICEA, Università di Padova, Padova, Italy.
| | - Enrico Bertuzzo
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Environmental Sciences, Informatics and Statistics, University Cà Foscari Venice, Venezia Mestre, Italy
| | - Melanie Blokesch
- Laboratory of Molecular Microbiology, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Lorenzo Mari
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
| | - Marino Gatto
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
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47
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Brouwer AF, Weir MH, Eisenberg MC, Meza R, Eisenberg JNS. Dose-response relationships for environmentally mediated infectious disease transmission models. PLoS Comput Biol 2017; 13:e1005481. [PMID: 28388665 PMCID: PMC5400279 DOI: 10.1371/journal.pcbi.1005481] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Revised: 04/21/2017] [Accepted: 03/27/2017] [Indexed: 11/18/2022] Open
Abstract
Environmentally mediated infectious disease transmission models provide a mechanistic approach to examining environmental interventions for outbreaks, such as water treatment or surface decontamination. The shift from the classical SIR framework to one incorporating the environment requires codifying the relationship between exposure to environmental pathogens and infection, i.e. the dose-response relationship. Much of the work characterizing the functional forms of dose-response relationships has used statistical fit to experimental data. However, there has been little research examining the consequences of the choice of functional form in the context of transmission dynamics. To this end, we identify four properties of dose-response functions that should be considered when selecting a functional form: low-dose linearity, scalability, concavity, and whether it is a single-hit model. We find that i) middle- and high-dose data do not constrain the low-dose response, and different dose-response forms that are equally plausible given the data can lead to significant differences in simulated outbreak dynamics; ii) the choice of how to aggregate continuous exposure into discrete doses can impact the modeled force of infection; iii) low-dose linear, concave functions allow the basic reproduction number to control global dynamics; and iv) identifiability analysis offers a way to manage multiple sources of uncertainty and leverage environmental monitoring to make inference about infectivity. By applying an environmentally mediated infectious disease model to the 1993 Milwaukee Cryptosporidium outbreak, we demonstrate that environmental monitoring allows for inference regarding the infectivity of the pathogen and thus improves our ability to identify outbreak characteristics such as pathogen strain.
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Affiliation(s)
- Andrew F. Brouwer
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
- * E-mail:
| | - Mark H. Weir
- Division of Environmental Health Sciences, The Ohio State University, Columbus, OH, United States of America
| | - Marisa C. Eisenberg
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
| | - Rafael Meza
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
| | - Joseph N. S. Eisenberg
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
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48
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Wu B, Mao S, Wang J, Zhou D. Control of epidemics via social partnership adjustment. Phys Rev E 2017; 94:062314. [PMID: 28085324 PMCID: PMC7217516 DOI: 10.1103/physreve.94.062314] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Indexed: 11/07/2022]
Abstract
Epidemic control is of great importance for human society. Adjusting interacting partners is an effective individualized control strategy. Intuitively, it is done either by shortening the interaction time between susceptible and infected individuals or by increasing the opportunities for contact between susceptible individuals. Here, we provide a comparative study on these two control strategies by establishing an epidemic model with nonuniform stochastic interactions. It seems that the two strategies should be similar, since shortening the interaction time between susceptible and infected individuals somehow increases the chances for contact between susceptible individuals. However, analytical results indicate that the effectiveness of the former strategy sensitively depends on the infectious intensity and the combinations of different interaction rates, whereas the latter one is quite robust and efficient. Simulations are shown to verify our analytical predictions. Our work may shed light on the strategic choice of disease control.
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Affiliation(s)
- Bin Wu
- School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, People's Republic of China
| | - Shanjun Mao
- School of Mathematical Sciences, Xiamen University, Xiamen 361005, People's Republic of China
| | - Jiazeng Wang
- Department of Mathematics, Beijing Technology and Business University, Beijing 100048, People's Republic of China
| | - Da Zhou
- School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computation, Xiamen University, Xiamen 361005, People's Republic of China
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49
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Oladokun MO, Okoh IA. Vibrio cholerae: A historical perspective and current trend. ASIAN PACIFIC JOURNAL OF TROPICAL DISEASE 2016. [DOI: 10.1016/s2222-1808(16)61154-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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50
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Santos-Vega M, Martinez PP, Pascual M. Climate forcing and infectious disease transmission in urban landscapes: integrating demographic and socioeconomic heterogeneity. Ann N Y Acad Sci 2016; 1382:44-55. [PMID: 27681053 DOI: 10.1111/nyas.13229] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Revised: 08/15/2016] [Accepted: 08/18/2016] [Indexed: 01/23/2023]
Abstract
Urbanization and climate change are the two major environmental challenges of the 21st century. The dramatic expansion of cities around the world creates new conditions for the spread, surveillance, and control of infectious diseases. In particular, urban growth generates pronounced spatial heterogeneity within cities, which can modulate the effect of climate factors at local spatial scales in large urban environments. Importantly, the interaction between environmental forcing and socioeconomic heterogeneity at local scales remains an open area in infectious disease dynamics, especially for urban landscapes of the developing world. A quantitative and conceptual framework on urban health with a focus on infectious diseases would benefit from integrating aspects of climate forcing, population density, and level of wealth. In this paper, we review what is known about these drivers acting independently and jointly on urban infectious diseases; we then outline elements that are missing and would contribute to building such a framework.
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Affiliation(s)
| | - Pamela P Martinez
- Ecology and Evolution Department, University of Chicago, Chicago, Illinois
| | - Mercedes Pascual
- Ecology and Evolution Department, University of Chicago, Chicago, Illinois
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