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Carrasco-Escobar G, Rosado J, Nolasco O, White MT, Mueller I, Castro MC, Rodriguez-Ferruci H, Gamboa D, Llanos-Cuentas A, Vinetz JM, Benmarhnia T. Effect of out-of-village working activities on recent malaria exposure in the Peruvian Amazon using parametric g-formula. Sci Rep 2022; 12:19144. [PMID: 36351988 PMCID: PMC9645738 DOI: 10.1038/s41598-022-23528-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 11/01/2022] [Indexed: 11/11/2022] Open
Abstract
In the Amazon Region of Peru, occupational activities are important drivers of human mobility and may increase the individual risk of being infected while contributing to increasing malaria community-level transmission. Even though out-of-village working activities and other mobility patterns have been identified as determinants of malaria transmission, no studies have quantified the effect of out-of-village working activities on recent malaria exposure and proposed plausible intervention scenarios. Using two population-based cross-sectional studies in the Loreto Department in Peru, and the parametric g-formula method, we simulated various hypothetical scenarios intervening in out-of-village working activities to reflect their potential health benefits. This study estimated that the standardized mean outcome (malaria seroprevalence) in the unexposed population (no out-of-village workers) was 44.6% (95% CI: 41.7%-47.5%) and 66.7% (95% CI: 61.6%-71.8%) in the exposed population resulting in a risk difference of 22.1% (95% CI: 16.3%-27.9%). However, heterogeneous patterns in the effects of interest were observed between peri-urban and rural areas (Cochran's Q test = 15.5, p < 0.001). Heterogeneous patterns were also observed in scenarios of increased prevalence of out-of-village working activities and restriction scenarios by gender (male vs. female) and age (18 and under vs. 19 and older) that inform possible occupational interventions targetting population subgroups. The findings of this study support the hypothesis that targeting out-of-village workers will considerably benefit current malaria elimination strategies in the Amazon Region. Particularly, males and adult populations that carried out out-of-village working activities in rural areas contribute the most to the malaria seropositivity (recent exposure to the parasite) in the Peruvian Amazon.
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Affiliation(s)
- Gabriel Carrasco-Escobar
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA.
- Health Innovation Lab, Institute of Tropical Medicine "Alexander Von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru.
| | - Jason Rosado
- G5 Épidémiologie Et Analyse Des Maladies Infectieuses, Département de Santé Globale, Institut Pasteur, 75015, Paris, France
| | - Oscar Nolasco
- Instituto de Medicina Tropical Alexander Von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación Y Desarrollo, Facultad de Ciencias Y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Michael T White
- G5 Épidémiologie Et Analyse Des Maladies Infectieuses, Département de Santé Globale, Institut Pasteur, 75015, Paris, France
| | - Ivo Mueller
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
- Population Health and Immunity Division, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
| | - Marcia C Castro
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Dionicia Gamboa
- Instituto de Medicina Tropical Alexander Von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación Y Desarrollo, Facultad de Ciencias Y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
- Departamento de Ciencias Celulares Y Moleculares, Facultad de Ciencias Y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Alejandro Llanos-Cuentas
- Instituto de Medicina Tropical Alexander Von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Joseph M Vinetz
- Instituto de Medicina Tropical Alexander Von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación Y Desarrollo, Facultad de Ciencias Y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Tarik Benmarhnia
- Scripps Institution of Oceanography, University of California, San Diego, CA, 92037, USA
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2
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Torres K, Ferreira MU, Castro MC, Escalante AA, Conn JE, Villasis E, da Silva Araujo M, Almeida G, Rodrigues PT, Corder RM, Fernandes ARJ, Calil PR, Ladeia WA, Garcia-Castillo SS, Gomez J, do Valle Antonelli LR, Gazzinelli RT, Golenbock DT, Llanos-Cuentas A, Gamboa D, Vinetz JM. Malaria Resilience in South America: Epidemiology, Vector Biology, and Immunology Insights from the Amazonian International Center of Excellence in Malaria Research Network in Peru and Brazil. Am J Trop Med Hyg 2022; 107:168-181. [PMID: 36228921 PMCID: PMC9662219 DOI: 10.4269/ajtmh.22-0127] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 05/28/2022] [Indexed: 11/07/2022] Open
Abstract
The 1990s saw the rapid reemergence of malaria in Amazonia, where it remains an important public health priority in South America. The Amazonian International Center of Excellence in Malaria Research (ICEMR) was designed to take a multidisciplinary approach toward identifying novel malaria control and elimination strategies. Based on geographically and epidemiologically distinct sites in the Northeastern Peruvian and Western Brazilian Amazon regions, synergistic projects integrate malaria epidemiology, vector biology, and immunology. The Amazonian ICEMR's overarching goal is to understand how human behavior and other sociodemographic features of human reservoirs of transmission-predominantly asymptomatically parasitemic people-interact with the major Amazonian malaria vector, Nyssorhynchus (formerly Anopheles) darlingi, and with human immune responses to maintain malaria resilience and continued endemicity in a hypoendemic setting. Here, we will review Amazonian ICEMR's achievements on the synergies among malaria epidemiology, Plasmodium-vector interactions, and immune response, and how those provide a roadmap for further research, and, most importantly, point toward how to achieve malaria control and elimination in the Americas.
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Affiliation(s)
- Katherine Torres
- Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Marcelo U. Ferreira
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, Sao Paulo, Brazil
| | - Marcia C. Castro
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Ananias A. Escalante
- Department of Biology and Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania
| | - Jan E. Conn
- Department of Biomedical Sciences, School of Public Health, University at Albany, State University of New York, Albany, New York
- Wadsworth Center, New York State Department of Health, Albany, New York
| | - Elizabeth Villasis
- Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Gregorio Almeida
- Instituto de Pesquisas Rene Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Brazil
| | - Priscila T. Rodrigues
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, Sao Paulo, Brazil
| | - Rodrigo M. Corder
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, Sao Paulo, Brazil
| | - Anderson R. J. Fernandes
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, Sao Paulo, Brazil
| | - Priscila R. Calil
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, Sao Paulo, Brazil
| | - Winni A. Ladeia
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, Sao Paulo, Brazil
| | - Stefano S. Garcia-Castillo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Joaquin Gomez
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Ricardo T. Gazzinelli
- Instituto de Pesquisas Rene Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Brazil
- Division of Infectious Disease and Immunology, Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Douglas T. Golenbock
- Division of Infectious Disease and Immunology, Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Alejandro Llanos-Cuentas
- Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Dionicia Gamboa
- Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Joseph M. Vinetz
- Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Address correspondence to Joseph M. Vinetz, Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, 25 York St., Winchester 403D, PO Box 802022, New Haven, CT 06520. E-mail:
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Carrasco-Escobar G, Matta-Chuquisapon J, Manrique E, Ruiz-Cabrejos J, Barboza JL, Wong D, Henostroza G, Llanos-Cuentas A, Benmarhnia T. Quantifying the effect of human population mobility on malaria risk in the Peruvian Amazon. ROYAL SOCIETY OPEN SCIENCE 2022; 9:211611. [PMID: 35875474 PMCID: PMC9297009 DOI: 10.1098/rsos.211611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 06/29/2022] [Indexed: 06/15/2023]
Abstract
The impact of human population movement (HPM) on the epidemiology of vector-borne diseases, such as malaria, has been described. However, there are limited data on the use of new technologies for the study of HPM in endemic areas with difficult access such as the Amazon. In this study conducted in rural Peruvian Amazon, we used self-reported travel surveys and GPS trackers coupled with a Bayesian spatial model to quantify the role of HPM on malaria risk. By using a densely sampled population cohort, this study highlighted the elevated malaria transmission in a riverine community of the Peruvian Amazon. We also found that the high connectivity between Amazon communities for reasons such as work, trading or family plausibly sustains such transmission levels. Finally, by using multiple human mobility metrics including GPS trackers, and adapted causal inference methods we identified for the first time the effect of human mobility patterns on malaria risk in rural Peruvian Amazon. This study provides evidence of the causal effect of HPM on malaria that may help to adapt current malaria control programmes in the Amazon.
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Affiliation(s)
- Gabriel Carrasco-Escobar
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Jose Matta-Chuquisapon
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Edgar Manrique
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jorge Ruiz-Cabrejos
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jose Luis Barboza
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Daniel Wong
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Alejandro Llanos-Cuentas
- Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Facultad de Salud Pública y Administración, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Tarik Benmarhnia
- Scripps Institution of Oceanography, University of California, San Diego, CA, USA
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Venkatesh U, Gandhi P A, Ara T, Rahman MM, Kishore J. Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries. Healthc Inform Res 2022; 28:160-169. [PMID: 35576984 PMCID: PMC9117801 DOI: 10.4258/hir.2022.28.2.160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 03/30/2022] [Indexed: 12/24/2022] Open
Abstract
Objectives During the coronavirus disease 2019 (COVID-19) pandemic, countries around the world framed specific laws and imposed varying degrees of lockdowns to ensure the maintenance of physical distancing. Understanding changes in temporal and spatial mobility patterns may provide insights into the dynamics of this infectious disease. Therefore, we assessed the efficacy of lockdown measures in 16 countries worldwide by analyzing the relationship between community mobility patterns and the doubling time of COVID-19. Methods We performed a retrospective record-based analysis of population-level data on the doubling time for COVID-19 and community mobility. The doubling time for COVID-19 was calculated based on the laboratory-confirmed cases reported daily over the study period (from February 15 to May 2, 2020). Principal component analysis (PCA) of six mobility pattern-related variables was conducted. To explain the magnitude of the effect of mobility on the doubling time, a finite linear distributed lag model was fitted. The k-means clustering approach was employed to identify countries with similar patterns in the significant co-efficient of the mobility index, with the optimal number of clusters derived using Elbow’s method. Results The countries analyzed had reduced mobility in commercial and social places. Reduced mobility had a significant and favorable association with the doubling time of COVID-19—specifically, the greater the mobility reduction, the longer the time taken for the COVID-19 cases to double. Conclusions COVID-19 lockdowns achieved the immediate objective of mobility reduction in countries with a high burden of cases.
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Affiliation(s)
- U Venkatesh
- Department of Community Medicine & Family Medicine, All India Institute of Medical Sciences, Gorakhpur,
India
| | - Aravind Gandhi P
- Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh,
India
| | - Tasnim Ara
- Institute of Statistical Research & Training, University of Dhaka, Dhaka,
Bangladesh
| | - Md Mahabubur Rahman
- Institute of Statistical Research & Training, University of Dhaka, Dhaka,
Bangladesh
| | - Jugal Kishore
- Department of Community Medicine, Vardhman Mahavir Medical College & Safdarjung Hospital, New Delhi,
India
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Periyasamy AG, Venkatesh U. Population Mobility, Lockdowns, and COVID-19 Control: An Analysis Based on Google Location Data and Doubling Time from India. Healthc Inform Res 2021; 27:325-334. [PMID: 34788913 PMCID: PMC8654337 DOI: 10.4258/hir.2021.27.4.325] [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: 02/16/2021] [Accepted: 08/23/2021] [Indexed: 12/24/2022] Open
Abstract
Objectives Physical distancing is a control measure against coronavirus disease 2019 (COVID-19). Lockdowns are a strategy to enforce physical distancing in urban areas, but they are drastic measures. Therefore, we assessed the effectiveness of the lockdown measures taken in the world’s second-most populous country, India, by exploring their relationship with community mobility patterns and the doubling time of COVID-19. Methods We conducted a retrospective analysis based on community mobility patterns, the stringency index of lockdown measures, and the doubling time of COVID-19 cases in India between February 15 and April 26, 2020. Pearson correlation coefficients were calculated between the stringency index, community mobility patterns, and the doubling time of COVID-19 cases. Multiple linear regression was applied to predict the doubling time of COVID-19. Results Community mobility drastically fell after the lockdown was instituted. The doubling time of COVID-19 cases was negatively correlated with population mobility patterns in outdoor areas (r = −0.45 to −0.58). The stringency index and outdoor mobility patterns were also negatively correlated (r = −0.89 to −0.95). Population mobility patterns (R2 = 0.67) were found to predict the doubling time of COVID-19, and the model’s predictive power increased when the stringency index was also added (R2 = 0.73). Conclusions Lockdown measures could effectively ensure physical distancing and reduce short-term case spikes in India. Therefore, lockdown measures may be considered for tailored implementation on an intermittent basis, whenever COVID-19 cases are predicted to exceed the health care system’s capacity to manage.
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Affiliation(s)
- Aravind Gandhi Periyasamy
- Department of Community Medicine, School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - U Venkatesh
- Department of Community Medicine, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India
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6
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Cuenca PR, Key S, Jumail A, Surendra H, Ferguson HM, Drakeley CJ, Fornace K. Epidemiology of the zoonotic malaria Plasmodium knowlesi in changing landscapes. ADVANCES IN PARASITOLOGY 2021; 113:225-286. [PMID: 34620384 DOI: 10.1016/bs.apar.2021.08.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Within the past two decades, incidence of human cases of the zoonotic malaria Plasmodium knowlesi has increased markedly. P. knowlesi is now the most common cause of human malaria in Malaysia and threatens to undermine malaria control programmes across Southeast Asia. The emergence of zoonotic malaria corresponds to a period of rapid deforestation within this region. These environmental changes impact the distribution and behaviour of the simian hosts, mosquito vector species and human populations, creating new opportunities for P. knowlesi transmission. Here, we review how landscape changes can drive zoonotic disease emergence, examine the extent and causes of these changes across Southeast and identify how these mechanisms may be impacting P. knowlesi dynamics. We review the current spatial epidemiology of reported P. knowlesi infections in people and assess how these demographic and environmental changes may lead to changes in transmission patterns. Finally, we identify opportunities to improve P. knowlesi surveillance and develop targeted ecological interventions within these landscapes.
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Affiliation(s)
- Pablo Ruiz Cuenca
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Stephanie Key
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | | | - Henry Surendra
- Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia; Centre for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Heather M Ferguson
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Chris J Drakeley
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Kimberly Fornace
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom; Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, Scotland, United Kingdom.
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Tam G, Cowling BJ, Maude RJ. Analysing human population movement data for malaria control and elimination. Malar J 2021; 20:294. [PMID: 34193167 PMCID: PMC8247220 DOI: 10.1186/s12936-021-03828-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/22/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Human population movement poses a major obstacle to malaria control and elimination. With recent technological advances, a wide variety of data sources and analytical methods have been used to quantify human population movement (HPM) relevant to control and elimination of malaria. METHODS The relevant literature and selected studies that had policy implications that could help to design or target malaria control and elimination interventions were reviewed. These studies were categorized according to spatiotemporal scales of human mobility and the main method of analysis. RESULTS Evidence gaps exist for tracking routine cross-border HPM and HPM at a regional scale. Few studies accounted for seasonality. Out of twenty included studies, two studies which tracked daily neighbourhood HPM used descriptive analyses as the main method, while the remaining studies used statistical analyses or mathematical modelling. CONCLUSION Although studies quantified varying types of human population movement covering different spatial and temporal scales, methodological gaps remain that warrant further studies related to malaria control and elimination.
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Affiliation(s)
- Greta Tam
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing, Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing, Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Richard J Maude
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand. .,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LG, UK. .,The Open University, Milton Keynes, MK7 6AA, UK. .,Harvard TH Chan School of Public Health, Harvard University, Boston, MA, 02115, USA.
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Auburn S, Cheng Q, Marfurt J, Price RN. The changing epidemiology of Plasmodium vivax: Insights from conventional and novel surveillance tools. PLoS Med 2021; 18:e1003560. [PMID: 33891580 PMCID: PMC8064506 DOI: 10.1371/journal.pmed.1003560] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Sarah Auburn and co-authors discuss the unique biology and epidemiology of P. vivax and current evidence on conventional and new approaches to surveillance.
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Affiliation(s)
- Sarah Auburn
- Global and Tropical Health Division, Menzies School of Health Research and Charles Darwin University, Darwin, Australia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand
| | - Qin Cheng
- Department of Drug Resistance and Diagnostics, Australian Defence Force Malaria and Infectious Disease Institute, Brisbane, Australia
- The Australian Defence Force Malaria and Infectious Disease Institute Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jutta Marfurt
- Global and Tropical Health Division, Menzies School of Health Research and Charles Darwin University, Darwin, Australia
| | - Ric N. Price
- Global and Tropical Health Division, Menzies School of Health Research and Charles Darwin University, Darwin, Australia
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand
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Rodríguez DM, Ryff K, Sánchez-Gonzalez L, Rivera-Amill V, Paz-Bailey G, Adams L. HTrack: A new tool to facilitate public health field visits and electronic data capture. PLoS One 2020; 15:e0244028. [PMID: 33320896 PMCID: PMC7737954 DOI: 10.1371/journal.pone.0244028] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 12/01/2020] [Indexed: 11/30/2022] Open
Abstract
Many applications have been developed for electronic data collection. However, offline field navigation tools incorporating secure electronic data capture and field visit tracking are currently scarce. We created an R-Shiny application, HTrack (Household Tracking), for use on encrypted Android devices in the field. The application was implemented in the Communities Organized to Prevent Arboviruses (COPA) project, a study beginning in 2018 to better understand arboviral disease incidence in 38 communities in Puerto Rico. The application was used to navigate to randomly selected structures and capture visit outcomes after conducting multiple visits for participant recruitment. It also served as a bridge to an alternate software, Epi Info, to collect participant-level questionnaire data. This application successfully captured each visit outcome and improved the logistics of field level activities for the COPA project, eliminating the use of paper maps for navigation. We show the development of HTrack and comment on the limitations and strengths of this application and further improvements.
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Affiliation(s)
- Dania M. Rodríguez
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
- * E-mail:
| | - Kyle Ryff
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Liliana Sánchez-Gonzalez
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | | | - Gabriela Paz-Bailey
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Laura Adams
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
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Malaria Transmission and Spillover across the Peru-Ecuador Border: A Spatiotemporal Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17207434. [PMID: 33066022 PMCID: PMC7600436 DOI: 10.3390/ijerph17207434] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/04/2020] [Accepted: 10/06/2020] [Indexed: 11/24/2022]
Abstract
Border regions have been implicated as important hot spots of malaria transmission, particularly in Latin America, where free movement rights mean that residents can cross borders using just a national ID. Additionally, rural livelihoods largely depend on short-term migrants traveling across borders via the Amazon’s river networks to work in extractive industries, such as logging. As a result, there is likely considerable spillover across country borders, particularly along the border between Peru and Ecuador. This border region exhibits a steep gradient of transmission intensity, with Peru having a much higher incidence of malaria than Ecuador. In this paper, we integrate 13 years of weekly malaria surveillance data collected at the district level in Peru and the canton level in Ecuador, and leverage hierarchical Bayesian spatiotemporal regression models to identify the degree to which malaria transmission in Ecuador is influenced by transmission in Peru. We find that increased case incidence in Peruvian districts that border the Ecuadorian Amazon is associated with increased incidence in Ecuador. Our results highlight the importance of coordinated malaria control across borders.
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11
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Carrasco-Escobar G, Fornace K, Wong D, Padilla-Huamantinco PG, Saldaña-Lopez JA, Castillo-Meza OE, Caballero-Andrade AE, Manrique E, Ruiz-Cabrejos J, Barboza JL, Rodriguez H, Henostroza G, Gamboa D, Castro MC, Vinetz JM, Llanos-Cuentas A. Open-Source 3D Printable GPS Tracker to Characterize the Role of Human Population Movement on Malaria Epidemiology in River Networks: A Proof-of-Concept Study in the Peruvian Amazon. Front Public Health 2020; 8:526468. [PMID: 33072692 PMCID: PMC7542225 DOI: 10.3389/fpubh.2020.526468] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 08/21/2020] [Indexed: 11/13/2022] Open
Abstract
Human movement affects malaria epidemiology at multiple geographical levels; however, few studies measure the role of human movement in the Amazon Region due to the challenging conditions and cost of movement tracking technologies. We developed an open-source low-cost 3D printable GPS-tracker and used this technology in a cohort study to characterize the role of human population movement in malaria epidemiology in a rural riverine village in the Peruvian Amazon. In this pilot study of 20 participants (mean age = 40 years old), 45,980 GPS coordinates were recorded over 1 month. Characteristic movement patterns were observed relative to the infection status and occupation of the participants. Applying two analytical animal movement ecology methods, utilization distributions (UDs) and integrated step selection functions (iSSF), we showed contrasting environmental selection and space use patterns according to infection status. These data suggested an important role of human movement in the epidemiology of malaria in the Peruvian Amazon due to high connectivity between villages of the same riverine network, suggesting limitations of current community-based control strategies. We additionally demonstrate the utility of this low-cost technology with movement ecology analysis to characterize human movement in resource-poor environments.
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Affiliation(s)
- Gabriel Carrasco-Escobar
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru.,Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA, United States.,Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Kimberly Fornace
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Daniel Wong
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Pierre G Padilla-Huamantinco
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru.,Departamento de Ingenieria, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jose A Saldaña-Lopez
- Departamento de Ingenieria, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Ober E Castillo-Meza
- Departamento de Ingenieria, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Armando E Caballero-Andrade
- Departamento de Ingenieria, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Edgar Manrique
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru.,Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jorge Ruiz-Cabrejos
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru.,Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jose Luis Barboza
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - German Henostroza
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Dionicia Gamboa
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru.,Departamento de Ciencias Celulares y Moleculares, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru.,Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Marcia C Castro
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - Joseph M Vinetz
- Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.,Section of Infectious Diseases, Yale School of Medicine, New Haven, CT, United States
| | - Alejandro Llanos-Cuentas
- Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.,Facultad de Salud Pública y Administración, Universidad Peruana Cayetano Heredia, Lima, Peru
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12
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Agbehadji IE, Awuzie BO, Ngowi AB, Millham RC. Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E5330. [PMID: 32722154 PMCID: PMC7432484 DOI: 10.3390/ijerph17155330] [Citation(s) in RCA: 78] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/24/2020] [Accepted: 06/29/2020] [Indexed: 12/23/2022]
Abstract
The emergence of the 2019 novel coronavirus (COVID-19) which was declared a pandemic has spread to 210 countries worldwide. It has had a significant impact on health systems and economic, educational and social facets of contemporary society. As the rate of transmission increases, various collaborative approaches among stakeholders to develop innovative means of screening, detecting and diagnosing COVID-19's cases among human beings at a commensurate rate have evolved. Further, the utility of computing models associated with the fourth industrial revolution technologies in achieving the desired feat has been highlighted. However, there is a gap in terms of the accuracy of detection and prediction of COVID-19 cases and tracing contacts of infected persons. This paper presents a review of computing models that can be adopted to enhance the performance of detecting and predicting the COVID-19 pandemic cases. We focus on big data, artificial intelligence (AI) and nature-inspired computing (NIC) models that can be adopted in the current pandemic. The review suggested that artificial intelligence models have been used for the case detection of COVID-19. Similarly, big data platforms have also been applied for tracing contacts. However, the nature-inspired computing (NIC) models that have demonstrated good performance in feature selection of medical issues are yet to be explored for case detection and tracing of contacts in the current COVID-19 pandemic. This study holds salient implications for practitioners and researchers alike as it elucidates the potentials of NIC in the accurate detection of pandemic cases and optimized contact tracing.
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Affiliation(s)
- Israel Edem Agbehadji
- Office of the Deputy Vice Chancellor: Research, Innovation and Engagement, Central University of Technology, Bloemfontein 9301, South Africa;
| | - Bankole Osita Awuzie
- Centre for Sustainable Smart Cities 4.0, Faculty of Engineering, Built Environment and Information Technology, Central University of Technology, Bloemfontein 9301, South Africa;
| | - Alfred Beati Ngowi
- Office of the Deputy Vice Chancellor: Research, Innovation and Engagement, Central University of Technology, Bloemfontein 9301, South Africa;
| | - Richard C. Millham
- ICT and Society Research Group, Department of Information Technology, Durban University of Technology, Durban 4001, South Africa;
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