Mapping imported malaria in Bangladesh using parasite genetic and human mobility data
- Harvard T H Chan School of Public Health, United States
- Johns Hopkins Bloomberg School of Public Health, United States
- Mahidol University, Thailand
- Wellcome Sanger Institute, United Kingdom
- Chittagong Medical College, Bangladesh
- Chittagong Medical College Hospital, Bangladesh
- Shaheed Suhrawardy Medical College, Bangladesh
- BRAC Centre, Bangladesh
- National Malaria Elimination Programme, Bangladesh
- World Health Organization, Bangladesh
- Directorate General of Health Services, Bangladesh
- The WorldWide Antimalarial Resistance Network (WWARN), Thailand
- Telenor Group, Norway
Abstract
For countries aiming for malaria elimination, travel of infected individuals between endemic areas undermines local interventions. Quantifying parasite importation has therefore become a priority for national control programs. We analyzed epidemiological surveillance data, travel surveys, parasite genetic data, and anonymized mobile phone data to measure the spatial spread of malaria parasites in southeast Bangladesh. We developed a genetic mixing index to estimate the likelihood of samples being local or imported from parasite genetic data and inferred the direction and intensity of parasite flow between locations using an epidemiological model integrating the travel survey and mobile phone calling data. Our approach indicates that, contrary to dogma, frequent mixing occurs in low transmission regions in the southwest, and elimination will require interventions in addition to reducing imported infections from forested regions. Unlike risk maps generated from clinical case counts alone, therefore, our approach distinguishes areas of frequent importation as well as high transmission.
Data availability
All genetic data are included in Supplementary file 4 and all travel matrices are included in Supplementary file 5.
Article and author information
Author details
Funding
National Institute of General Medical Sciences (U54GM088558)
- Hsiao-Han Chang
Burroughs Wellcome Fund
- Amy Wesolowski
Bill and Melinda Gates Foundation (CPT000390)
- Ipsita Sinha
- Sazid Ibna Zaman
- Richard J Maude
Medical Research Council (G0600718)
- Christopher G Jacob
- Eleanor Drury
- Sonia Gonçalves
- Mihir Kekre
- Dominic Kwiatkowski
National Institute of General Medical Sciences (R35GM124715-02)
- Caroline Buckee
Bill and Melinda Gates Foundation (OPP1118166)
- Christopher G Jacob
- Olivo Miotto
- Caroline Buckee
Bill and Melinda Gates Foundation (OPP1129596)
- Ipsita Sinha
- Sazid Ibna Zaman
- Richard J Maude
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Chang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 4,140
- views
-
- 603
- downloads
-
- 84
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Mapping imported malaria in Bangladesh using parasite genetic and human mobility data
eLife 8:e43481.
https://doi.org/10.7554/eLife.43481
Further reading
-
- Epidemiology and Global Health
- Microbiology and Infectious Disease
Lack of data on the aetiology of livestock diseases constrains effective interventions to improve livelihoods, food security and public health. Livestock abortion is an important disease syndrome affecting productivity and public health. Several pathogens are associated with livestock abortions but across Africa surveillance data rarely include information from abortions, little is known about aetiology and impacts, and data are not available to inform interventions. This paper describes outcomes from a surveillance platform established in Tanzania spanning pastoral, agropastoral and smallholder systems to investigate causes and impacts of livestock abortion. Abortion events were reported by farmers to livestock field officers (LFO) and on to investigation teams. Events were included if the research team or LFO could attend within 72 hr. If so, samples and questionnaire data were collected to investigate (a) determinants of attribution; (b) patterns of events, including species and breed, previous abortion history, and seasonality; (c) determinants of reporting, investigation and attribution; (d) cases involving zoonotic pathogens. Between 2017–2019, 215 events in cattle (n=71), sheep (n=44), and goats (n=100) were investigated. Attribution, achieved for 19.5% of cases, was significantly affected by delays in obtaining samples. Histopathology proved less useful than PCR due to rapid deterioration of samples. Vaginal swabs provided practical and sensitive material for pathogen detection. Livestock abortion surveillance, even at a small scale, can generate valuable information on causes of disease outbreaks, reproductive losses and can identify pathogens not easily captured through other forms of livestock disease surveillance. This study demonstrated the feasibility of establishing a surveillance system, achieved through engagement of community-based field officers, establishment of practical sample collection and application of molecular diagnostic platforms.
-
- Epidemiology and Global Health
- Genetics and Genomics
Alzheimer’s disease (AD) is a complex degenerative disease of the central nervous system, and elucidating its pathogenesis remains challenging. In this study, we used the inverse-variance weighted (IVW) model as the major analysis method to perform hypothesis-free Mendelian randomization (MR) analysis on the data from MRC IEU OpenGWAS (18,097 exposure traits and 16 AD outcome traits), and conducted sensitivity analysis with six models, to assess the robustness of the IVW results, to identify various classes of risk or protective factors for AD, early-onset AD, and late-onset AD. We generated 400,274 data entries in total, among which the major analysis method of the IVW model consists of 73,129 records with 4840 exposure traits, which fall into 10 categories: Disease, Medical laboratory science, Imaging, Anthropometric, Treatment, Molecular trait, Gut microbiota, Past history, Family history, and Lifestyle trait. More importantly, a freely accessed online platform called MRAD (https://gwasmrad.com/mrad/) has been developed using the Shiny package with MR analysis results. Additionally, novel potential AD therapeutic targets (CD33, TBCA, VPS29, GNAI3, PSME1) are identified, among which CD33 was positively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. TBCA and VPS29 were negatively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. GNAI3 and PSME1 were negatively associated with the main outcome traits of AD, as well as with LOAD, but had no significant causal association with EOAD. The findings of our research advance our understanding of the etiology of AD.
