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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] [MESH Headings] [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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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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Shackleton D, Memon FA, Chen A, Dutta S, Kanungo S, Deb A. The changing relationship between Cholera and interannual climate variables in Kolkata over the past century. Gut Pathog 2023; 15:42. [PMID: 37704999 PMCID: PMC10498578 DOI: 10.1186/s13099-023-00565-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 08/01/2023] [Indexed: 09/15/2023] Open
Abstract
BACKGROUND In the Bengal Delta, research has shown that climate and cholera are linked. One demonstration of this is the relationship between interannual ocean-atmospheric oscillations such as the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). What remains unclear in the present literature is the nature of this relationship in the specific context of Kolkata, and how this relationship may have changed over time. RESULTS In this study, we analyse the changing relationship between ENSO and IOD with cholera in Kolkata over recent (1999-2019) and historical (1897-1941) time intervals. Wavelet coherence analysis revealed significant non-stationary association at 2-4 year and 4-8 year periods between cholera and both interannual timeseries during both time intervals. However, coherence was notably weakened in the recent interval, particularly with regards to ENSO, a result supported by a complementary SARIMA analysis. Similar coherence patterns with temperature indicate it could be an important mediating factor in the relationship between cholera and oscillating climate phenomena in Kolkata. CONCLUSIONS This study reveals a shifting relationship between cholera and climate variables (ENSO and IOD) in Kolkata, suggesting a decoupling between environmental influences and cholera transmission in recent years. Our results therefore do not suggest that an intensification of ENSO is likely to significantly influence cholera in the region. We also find that the relationship between cholera and interannual climate variables is distinct to Kolkata, highlighting the spatial heterogeneity of the climate-cholera relationship even within the Bengal Delta.
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Affiliation(s)
- Debbie Shackleton
- Centre for Water Systems, Department of Engineering, University of Exeter, EX4 4QF, Exeter, UK.
| | - Fayyaz Ali Memon
- Centre for Water Systems, Department of Engineering, University of Exeter, EX4 4QF, Exeter, UK
| | - Albert Chen
- Centre for Water Systems, Department of Engineering, University of Exeter, EX4 4QF, Exeter, UK
| | - Shanta Dutta
- National Institute of Cholera and Enteric Diseases, Kolkata, India
| | - Suman Kanungo
- National Institute of Cholera and Enteric Diseases, Kolkata, India
| | - Alok Deb
- National Institute of Cholera and Enteric Diseases, Kolkata, India
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Usmani M, Brumfield KD, Jamal Y, Huq A, Colwell RR, Jutla A. A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera. Trop Med Infect Dis 2021; 6:tropicalmed6030147. [PMID: 34449728 PMCID: PMC8396309 DOI: 10.3390/tropicalmed6030147] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 07/29/2021] [Accepted: 07/31/2021] [Indexed: 11/16/2022] Open
Abstract
Climate variables influence the occurrence, growth, and distribution of Vibrio cholerae in the aquatic environment. Together with socio-economic factors, these variables affect the incidence and intensity of cholera outbreaks. The current pandemic of cholera began in the 1960s, and millions of cholera cases are reported each year globally. Hence, cholera remains a significant health challenge, notably where human vulnerability intersects with changes in hydrological and environmental processes. Cholera outbreaks may be epidemic or endemic, the mode of which is governed by trigger and transmission components that control the outbreak and spread of the disease, respectively. Traditional cholera risk assessment models, namely compartmental susceptible-exposed-infected-recovered (SEIR) type models, have been used to determine the predictive spread of cholera through the fecal–oral route in human populations. However, these models often fail to capture modes of infection via indirect routes, such as pathogen movement in the environment and heterogeneities relevant to disease transmission. Conversely, other models that rely solely on variability of selected environmental factors (i.e., examine only triggers) have accomplished real-time outbreak prediction but fail to capture the transmission of cholera within impacted populations. Since the mode of cholera outbreaks can transition from epidemic to endemic, a comprehensive transmission model is needed to achieve timely and reliable prediction with respect to quantitative environmental risk. Here, we discuss progression of the trigger module associated with both epidemic and endemic cholera, in the context of the autochthonous aquatic nature of the causative agent of cholera, V. cholerae, as well as disease prediction.
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Affiliation(s)
- Moiz Usmani
- Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL 32603, USA; (M.U.); (Y.J.); (A.J.)
| | - Kyle D. Brumfield
- Maryland Pathogen Research Institute, University of Maryland, College Park, MD 20742, USA; (K.D.B.); (A.H.)
- University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742, USA
| | - Yusuf Jamal
- Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL 32603, USA; (M.U.); (Y.J.); (A.J.)
| | - Anwar Huq
- Maryland Pathogen Research Institute, University of Maryland, College Park, MD 20742, USA; (K.D.B.); (A.H.)
| | - Rita R. Colwell
- Maryland Pathogen Research Institute, University of Maryland, College Park, MD 20742, USA; (K.D.B.); (A.H.)
- University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742, USA
- Correspondence:
| | - Antarpreet Jutla
- Geohealth and Hydrology Laboratory, Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL 32603, USA; (M.U.); (Y.J.); (A.J.)
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Nayna Schwerdtle P, Stockemer J, Bowen KJ, Sauerborn R, McMichael C, Danquah I. A Meta-Synthesis of Policy Recommendations Regarding Human Mobility in the Context of Climate Change. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E9342. [PMID: 33327439 PMCID: PMC7764877 DOI: 10.3390/ijerph17249342] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 12/04/2020] [Accepted: 12/10/2020] [Indexed: 02/06/2023]
Abstract
Changing mobility patterns combined with changes in the climate present challenges and opportunities for global health, requiring effective, relevant, and humane policy responses. This study used data from a systematic literature review that examined the intersection between climate change, migration, and health. The study aimed to synthesize policy recommendations in the peer-reviewed literature, regarding this type of environmental migration with respect to health, to strengthen the evidence-base. Systematic searches were conducted in four academic databases (PubMed, Ovid Medline, Global Health and Scopus) and Google Scholar for empirical studies published between 1990-2020 that used any study design to investigate migration and health in the context of climate change. Studies underwent a two-stage protocol-based screening process and eligible studies were appraised for quality using a standardized mixed-methods tool. From the initial 2425 hits, 68 articles were appraised for quality and included in the synthesis. Among the policy recommendations, six themes were discernible: (1) avoid the universal promotion of migration as an adaptive response to climate risk; (2) preserve cultural and social ties of mobile populations; (3) enable the participation of migrants in decision-making in sites of relocation and resettlement; (4) strengthen health systems and reduce barriers for migrant access to health care; (5) support and promote optimization of social determinants of migrant health; (6) integrate health into loss and damage assessments related to climate change, and consider immobile and trapped populations. The results call for transformative policies that support the health and wellbeing of people engaging in or affected by mobility responses, including those whose migration decisions and experiences are influenced by climate change, and to establish and develop inclusive migrant healthcare.
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Affiliation(s)
- Patricia Nayna Schwerdtle
- Heidelberg Institute of Global Health, Universitaetsklinikum Heidelberg, 69120 Heidelberg, Germany; (J.S.); (R.S.); (I.D.)
- Nursing & Midwifery, Faculty of Medicine, Nursing & Health Science, Monash University, Clayton, VIC 3800, Australia
| | - Julia Stockemer
- Heidelberg Institute of Global Health, Universitaetsklinikum Heidelberg, 69120 Heidelberg, Germany; (J.S.); (R.S.); (I.D.)
| | - Kathryn J. Bowen
- Fenner School of Environment and Society, and Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia;
- Institute for Advanced Sustainability Studies, 14467 Potsdam, Germany
- Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC 3010, Australia
| | - Rainer Sauerborn
- Heidelberg Institute of Global Health, Universitaetsklinikum Heidelberg, 69120 Heidelberg, Germany; (J.S.); (R.S.); (I.D.)
| | - Celia McMichael
- School of Geography, University of Melbourne, Parkville, VIC 3010, Australia;
| | - Ina Danquah
- Heidelberg Institute of Global Health, Universitaetsklinikum Heidelberg, 69120 Heidelberg, Germany; (J.S.); (R.S.); (I.D.)
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Traniello JFA, Bakker TCM. Social behavior and disease: supporting science during the pandemic. Behav Ecol Sociobiol 2020; 74:99. [PMID: 32834413 PMCID: PMC7367787 DOI: 10.1007/s00265-020-02882-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- James F A Traniello
- Department of Biology, Boston University, 5 Cummington Mall, Boston, MA 02215 USA
| | - Theo C M Bakker
- Institute for Evolutionary Biology and Ecology, University of Bonn, An der Immenburg 1, 53121 Bonn, Germany
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Ryckman T, Luby S, Owens DK, Bendavid E, Goldhaber-Fiebert JD. Methods for Model Calibration under High Uncertainty: Modeling Cholera in Bangladesh. Med Decis Making 2020; 40:693-709. [PMID: 32639859 DOI: 10.1177/0272989x20938683] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background. Published data on a disease do not always correspond directly to the parameters needed to simulate natural history. Several calibration methods have been applied to computer-based disease models to extract needed parameters that make a model's output consistent with available data. Objective. To assess 3 calibration methods and evaluate their performance in a real-world application. Methods. We calibrated a model of cholera natural history in Bangladesh, where a lack of active surveillance biases available data. We built a cohort state-transition cholera natural history model that includes case hospitalization to reflect the passive surveillance data-generating process. We applied 3 calibration techniques: incremental mixture importance sampling, sampling importance resampling, and random search with rejection sampling. We adapted these techniques to the context of wide prior uncertainty and many degrees of freedom. We evaluated the resulting posterior parameter distributions using a range of metrics and compared predicted cholera burden estimates. Results. All 3 calibration techniques produced posterior distributions with a higher likelihood and better fit to calibration targets as compared with prior distributions. Incremental mixture importance sampling resulted in the highest likelihood and largest number of unique parameter sets to better inform joint parameter uncertainty. Compared with naïve uncalibrated parameter sets, calibrated models of cholera in Bangladesh project substantially more cases, many of which are not detected by passive surveillance, and fewer deaths. Limitations. Calibration cannot completely overcome poor data quality, which can leave some parameters less well informed than others. Calibration techniques may perform differently under different circumstances. Conclusions. Incremental mixture importance sampling, when adapted to the context of high uncertainty, performs well. By accounting for biases in data, calibration can improve model projections of disease burden.
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Affiliation(s)
- Theresa Ryckman
- Center for Health Policy and Center for Primary Care & Outcomes Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Stephen Luby
- Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Douglas K Owens
- VA Palo Alto Healthcare System, Palo Alto, CA, USA.,Center for Health Policy and Center for Primary Care & Outcomes Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Eran Bendavid
- Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.,Center for Health Policy and Center for Primary Care & Outcomes Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Jeremy D Goldhaber-Fiebert
- Center for Health Policy and Center for Primary Care & Outcomes Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
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Lemaitre J, Pasetto D, Perez-Saez J, Sciarra C, Wamala JF, Rinaldo A. Rainfall as a driver of epidemic cholera: Comparative model assessments of the effect of intra-seasonal precipitation events. Acta Trop 2019; 190:235-243. [PMID: 30465744 DOI: 10.1016/j.actatropica.2018.11.013] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 11/04/2018] [Accepted: 11/14/2018] [Indexed: 01/18/2023]
Abstract
The correlation between cholera epidemics and climatic drivers, in particular seasonal tropical rainfall, has been studied in a variety of contexts owing to its documented relevance. Several mechanistic models of cholera transmission have included rainfall as a driver by focusing on two possible transmission pathways: either by increasing exposure to contaminated water (e.g. due to worsening sanitary conditions during water excess), or water contamination by freshly excreted bacteria (e.g. due to washout of open-air defecation sites or overflows). Our study assesses the explanatory power of these different modeling structures by formal model comparison using deterministic and stochastic models of the type susceptible-infected-recovered-bacteria (SIRB). The incorporation of rainfall effects is generalized using a nonlinear function that can increase or decrease the relative importance of the large precipitation events. Our modelling framework is tested against the daily epidemiological data collected during the 2015 cholera outbreak within the urban context of Juba, South Sudan. This epidemic is characterized by a particular intra-seasonal double peak on the incidence in apparent relation with particularly strong rainfall events. Our results show that rainfall-based models in both their deterministic and stochastic formulations outperform models that do not account for rainfall. In fact, classical SIRB models are not able to reproduce the second epidemiological peak, thus suggesting that it was rainfall-driven. Moreover we found stronger support across model types for rainfall acting on increased exposure rather than on exacerbated water contamination. Although these results are context-specific, they stress the importance of a systematic and comprehensive appraisal of transmission pathways and their environmental forcings when embarking in the modelling of epidemic cholera.
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Affiliation(s)
- Joseph Lemaitre
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
| | - Damiano Pasetto
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
| | - Javier Perez-Saez
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
| | - Carla Sciarra
- Dipartimento di Ingegneria dell'Ambiente, del Territorio e delle Infrastrutture, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.
| | | | - Andrea Rinaldo
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland; Dipartimento ICEA, Università di Padova, 35100 Padova, Italy.
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Martinez PP, Reiner RC, Cash BA, Rodó X, Shahjahan Mondal M, Roy M, Yunus M, Faruque ASG, Huq S, King AA, Pascual M. Cholera forecast for Dhaka, Bangladesh, with the 2015-2016 El Niño: Lessons learned. PLoS One 2017; 12:e0172355. [PMID: 28253325 PMCID: PMC5333828 DOI: 10.1371/journal.pone.0172355] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2016] [Accepted: 02/04/2017] [Indexed: 11/29/2022] Open
Abstract
A substantial body of work supports a teleconnection between the El Niño-Southern Oscillation (ENSO) and cholera incidence in Bangladesh. In particular, high positive anomalies during the winter (Dec-Feb) in sea surface temperatures (SST) in the tropical Pacific have been shown to exacerbate the seasonal outbreak of cholera following the monsoons from August to November. Climate studies have indicated a role of regional precipitation over Bangladesh in mediating this long-distance effect. Motivated by this previous evidence, we took advantage of the strong 2015-2016 El Niño event to evaluate the predictability of cholera dynamics for the city in recent times based on two transmission models that incorporate SST anomalies and are fitted to the earlier surveillance records starting in 1995. We implemented a mechanistic temporal model that incorporates both epidemiological processes and the effect of ENSO, as well as a previously published statistical model that resolves space at the level of districts (thanas). Prediction accuracy was evaluated with "out-of-fit" data from the same surveillance efforts (post 2008 and 2010 for the two models respectively), by comparing the total number of cholera cases observed for the season to those predicted by model simulations eight to twelve months ahead, starting in January each year. Although forecasts were accurate for the low cholera risk observed for the years preceding the 2015-2016 El Niño, the models also predicted a high probability of observing a large outbreak in fall 2016. Observed cholera cases up to Oct 2016 did not show evidence of an anomalous season. We discuss these predictions in the context of regional and local climate conditions, which show that despite positive regional rainfall anomalies, rainfall and inundation in Dhaka remained low. Possible explanations for these patterns are given together with future implications for cholera dynamics and directions to improve their prediction for the city.
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Affiliation(s)
- Pamela P. Martinez
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
| | - Robert C. Reiner
- Department of Epidemiology and Biostatistics, Indiana University Bloomington School of Public Health, Bloomington, Indiana, United States of America
| | - Benjamin A. Cash
- Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, Virginia, United States of America
| | - Xavier Rodó
- Catalan Institution for Research and Advanced Studies (ICREA), Catalunya, Spain
- Climate and Health Program, ISGlobal, Catalunya, Spain
| | - Mohammad Shahjahan Mondal
- Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Manojit Roy
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mohammad Yunus
- International Centre for Diarrheal Disease Research, Dhaka, Bangladesh
| | - A. S. G. Faruque
- International Centre for Diarrheal Disease Research, Dhaka, Bangladesh
| | - Sayeeda Huq
- International Centre for Diarrheal Disease Research, Dhaka, Bangladesh
| | - Aaron A. King
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Mathematics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mercedes Pascual
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
- Santa Fe Institute, Santa Fe, New Mexico, United States of America
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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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