Showing papers by "Peter W. Gething published in 2014"

Mapping the zoonotic niche of Ebola virus disease in Africa

Abstract: Ebola virus disease (EVD) is a complex zoonosis that is highly virulent in humans. The largest recorded outbreak of EVD is ongoing in West Africa, outside of its previously reported and predicted niche. We assembled location data on all recorded zoonotic transmission to humans and Ebola virus infection in bats and primates (1976-2014). Using species distribution models, these occurrence data were paired with environmental covariates to predict a zoonotic transmission niche covering 22 countries across Central and West Africa. Vegetation, elevation, temperature, evapotranspiration, and suspected reservoir bat distributions define this relationship. At-risk areas are inhabited by 22 million people; however, the rarity of human outbreaks emphasises the very low probability of transmission to humans. Increasing population sizes and international connectivity by air since the first detection of EVD in 1976 suggest that the dynamics of human-to-human secondary transmission in contemporary outbreaks will be very different to those of the past.

Global temperature constraints on Aedes aegypti and Ae. albopictus persistence and competence for dengue virus transmission

Abstract: Dengue is a disease that has undergone significant expansion over the past hundred years. Understanding what factors limit the distribution of transmission can be used to predict current and future limits to further dengue expansion. While not the only factor, temperature plays an important role in defining these limits. Previous attempts to analyse the effect of temperature on the geographic distribution of dengue have not considered its dynamic intra-annual and diurnal change and its cumulative effects on mosquito and virus populations. Here we expand an existing modelling framework with new temperature-based relationships to model an index proportional to the basic reproductive number of the dengue virus. This model framework is combined with high spatial and temporal resolution global temperature data to model the effects of temperature on Aedes aegypti and Ae. albopictus persistence and competence for dengue virus transmission. Our model predicted areas where temperature is not expected to permit transmission and/or Aedes persistence throughout the year. By reanalysing existing experimental data our analysis indicates that Ae. albopictus, often considered a minor vector of dengue, has comparable rates of virus dissemination to its primary vector, Ae. aegypti, and when the longer lifespan of Ae. albopictus is considered its competence for dengue virus transmission far exceeds that of Ae. aegypti. These results can be used to analyse the effects of temperature and other contributing factors on the expansion of dengue or its Aedes vectors. Our finding that Ae. albopictus has a greater capacity for dengue transmission than Ae. aegypti is contrary to current explanations for the comparative rarity of dengue transmission in established Ae. albopictus populations. This suggests that the limited capacity of Ae. albopictus to transmit DENV is more dependent on its ecology than vector competence. The recommendations, which we explicitly outlined here, point to clear targets for entomological investigation.

Geographical variation in Plasmodium vivax relapse

Abstract: Plasmodium vivax has the widest geographic distribution of the human malaria parasites and nearly 2.5 billion people live at risk of infection. The control of P. vivax in individuals and populations is complicated by its ability to relapse weeks to months after initial infection. Strains of P. vivax from different geographical areas are thought to exhibit varied relapse timings. In tropical regions strains relapse quickly (three to six weeks), whereas those in temperate regions do so more slowly (six to twelve months), but no comprehensive assessment of evidence has been conducted. Here observed patterns of relapse periodicity are used to generate predictions of relapse incidence within geographic regions representative of varying parasite transmission. A global review of reports of P. vivax relapse in patients not treated with a radical cure was conducted. Records of time to first P. vivax relapse were positioned by geographic origin relative to expert opinion regions of relapse behaviour and epidemiological zones. Mixed-effects meta-analysis was conducted to determine which geographic classification best described the data, such that a description of the pattern of relapse periodicity within each region could be described. Model outputs of incidence and mean time to relapse were mapped to illustrate the global variation in relapse. Differences in relapse periodicity were best described by a historical geographic classification system used to describe malaria transmission zones based on areas sharing zoological and ecological features. Maps of incidence and time to relapse showed high relapse frequency to be predominant in tropical regions and prolonged relapse in temperate areas. The results indicate that relapse periodicity varies systematically by geographic region and are categorized by nine global regions characterized by similar malaria transmission dynamics. This indicates that relapse may be an adaptation evolved to exploit seasonal changes in vector survival and therefore optimize transmission. Geographic patterns in P. vivax relapse are important to clinicians treating individual infections, epidemiologists trying to infer P. vivax burden, and public health officials trying to control and eliminate the disease in human populations.

Global distribution maps of the leishmaniases

Abstract: The leishmaniases are vector-borne diseases that have a broad global distribution throughout much of the Americas, Africa, and Asia. Despite representing a significant public health burden, our understanding of the global distribution of the leishmaniases remains vague, reliant upon expert opinion and limited to poor spatial resolution. A global assessment of the consensus of evidence for leishmaniasis was performed at a sub-national level by aggregating information from a variety of sources. A database of records of cutaneous and visceral leishmaniasis occurrence was compiled from published literature, online reports, strain archives, and GenBank accessions. These, with a suite of biologically relevant environmental covariates, were used in a boosted regression tree modelling framework to generate global environmental risk maps for the leishmaniases. These high-resolution evidence-based maps can help direct future surveillance activities, identify areas to target for disease control and inform future burden estimation efforts.

Geographical Inequalities in Use of Improved Drinking Water Supply and Sanitation across Sub-Saharan Africa: Mapping and Spatial Analysis of Cross-sectional Survey Data

Abstract: Background Understanding geographic inequalities in coverage of drinking-water supply and sanitation (WSS) will help track progress towards universal coverage of water and sanitation by identifying marginalized populations, thus helping to control a large number of infectious diseases. This paper uses household survey data to develop comprehensive maps of WSS coverage at high spatial resolution for sub-Saharan Africa (SSA). Analysis is extended to investigate geographic heterogeneity and relative geographic inequality within countries. Methods and Findings Cluster-level data on household reported use of improved drinking-water supply, sanitation, and open defecation were abstracted from 138 national surveys undertaken from 1991–2012 in 41 countries. Spatially explicit logistic regression models were developed and fitted within a Bayesian framework, and used to predict coverage at the second administrative level (admin2, e.g., district) across SSA for 2012. Results reveal substantial geographical inequalities in predicted use of water and sanitation that exceed urban-rural disparities. The average range in coverage seen between admin2 within countries was 55% for improved drinking water, 54% for use of improved sanitation, and 59% for dependence upon open defecation. There was also some evidence that countries with higher levels of inequality relative to coverage in use of an improved drinking-water source also experienced higher levels of inequality in use of improved sanitation (rural populations r = 0.47, p = 0.002; urban populations r = 0.39, p = 0.01). Results are limited by the quantity of WSS data available, which varies considerably by country, and by the reliability and utility of available indicators. Conclusions This study identifies important geographic inequalities in use of WSS previously hidden within national statistics, confirming the necessity for targeted policies and metrics that reach the most marginalized populations. The presented maps and analysis approach can provide a mechanism for monitoring future reductions in inequality within countries, reflecting priorities of the post-2015 development agenda. Please see later in the article for the Editors' Summary

An effective approach for gap-filling continental scale remotely sensed time-series

Abstract: The archives of imagery and modeled data products derived from remote sensing programs with high temporal resolution provide powerful resources for characterizing inter- and intra-annual environmental dynamics. The impressive depth of available time-series from such missions (e.g., MODIS and AVHRR) affords new opportunities for improving data usability by leveraging spatial and temporal information inherent to longitudinal geospatial datasets. In this research we develop an approach for filling gaps in imagery time-series that result primarily from cloud cover, which is particularly problematic in forested equatorial regions. Our approach consists of two, complementary gap-filling algorithms and a variety of run-time options that allow users to balance competing demands of model accuracy and processing time. We applied the gap-filling methodology to MODIS Enhanced Vegetation Index (EVI) and daytime and nighttime Land Surface Temperature (LST) datasets for the African continent for 2000–2012, with a 1 km spatial resolution, and an 8-day temporal resolution. We validated the method by introducing and filling artificial gaps, and then comparing the original data with model predictions. Our approach achieved R2 values above 0.87 even for pixels within 500 km wide introduced gaps. Furthermore, the structure of our approach allows estimation of the error associated with each gap-filled pixel based on the distance to the non-gap pixels used to model its fill value, thus providing a mechanism for including uncertainty associated with the gap-filling process in downstream applications of the resulting datasets.

Recasting the theory of mosquito-borne pathogen transmission dynamics and control

Abstract: Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of the world. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald's formula for R0 and its entomological derivative, vectorial capacity, are now used to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross-Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context for mosquito blood feeding, the movement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control.

Predicting the risk of avian influenza A H7N9 infection in live-poultry markets across Asia

Abstract: Two epidemic waves of an avian influenza A (H7N9) virus have so far affected China. Most human cases have been attributable to poultry exposure at live-poultry markets, where most positive isolates were sampled. The potential geographic extent of potential re-emerging epidemics is unknown, as are the factors associated with it. Using newly assembled data sets of the locations of 8,943 live-poultry markets in China and maps of environmental correlates, we develop a statistical model that accurately predicts the risk of H7N9 market infection across Asia. Local density of live-poultry markets is the most important predictor of H7N9 infection risk in markets, underscoring their key role in the spatial epidemiology of H7N9, alongside other poultry, land cover and anthropogenic predictor variables. Identification of areas in Asia with high suitability for H7N9 infection enhances our capacity to target biosurveillance and control, helping to restrict the spread of this important disease.

Defining the Geographical Range of the Plasmodium knowlesi Reservoir

Abstract: BACKGROUND: The simian malaria parasite, Plasmodium knowlesi, can cause severe and fatal disease in humans yet it is rarely included in routine public health reporting systems for malaria and its geographical range is largely unknown. Because malaria caused by P. knowlesi is a truly neglected tropical disease, there are substantial obstacles to defining the geographical extent and risk of this disease. Information is required on the occurrence of human cases in different locations, on which non-human primates host this parasite and on which vectors are able to transmit it to humans. We undertook a systematic review and ranked the existing evidence, at a subnational spatial scale, to investigate the potential geographical range of the parasite reservoir capable of infecting humans. METHODOLOGY/PRINCIPAL FINDINGS: After reviewing the published literature we identified potential host and vector species and ranked these based on how informative they are for the presence of an infectious parasite reservoir, based on current evidence. We collated spatial data on parasite occurrence and the ranges of the identified host and vector species. The ranked spatial data allowed us to assign an evidence score to 475 subnational areas in 19 countries and we present the results on a map of the Southeast and South Asia region. CONCLUSIONS/SIGNIFICANCE: We have ranked subnational areas within the potential disease range according to evidence for presence of a disease risk to humans, providing geographical evidence to support decisions on prevention, management and prophylaxis. This work also highlights the unknown risk status of large parts of the region. Within this unknown category, our map identifies which areas have most evidence for the potential to support an infectious reservoir and are therefore a priority for further investigation. Furthermore we identify geographical areas where further investigation of putative host and vector species would be highly informative for the region-wide assessment.

A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots

Abstract: Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or 'hotspots' of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance.DOI: http://dx.doi.org/10.7554/eLife.02130.001.

Air temperature suitability for Plasmodium falciparum malaria transmission in Africa 2000-2012: A high-resolution spatiotemporal prediction

Abstract: Temperature suitability for malaria transmission is a useful predictor variable for spatial models of malaria infection prevalence. Existing continental or global models, however, are synoptic in nature and so do not characterize inter-annual variability in seasonal patterns of temperature suitability, reducing their utility for predicting malaria risk. A malaria Temperature Suitability Index (TSI) was created by first modeling minimum and maximum air temperature with an eight-day temporal resolution from gap-filled MODerate Resolution Imaging Spectroradiometer (MODIS) daytime and night-time Land Surface Temperature (LST) datasets. An improved version of an existing biological model for malaria temperature suitability was then applied to the resulting temperature information for a 13-year data series. The mechanism underlying this biological model is simulation of emergent mosquito cohorts on a two-hour time-step and tracking of each cohort throughout its life to quantify the impact air temperature has on both mosquito survival and sporozoite development. The results of this research consist of 154 monthly raster surfaces that characterize spatiotemporal patterns in TSI across Africa from April 2000 through December 2012 at a 1 km spatial resolution. Generalized TSI patterns were as expected, with consistently high values in equatorial rain forests, seasonally variable values in tropical savannas (wet and dry) and montane areas, and low values in arid, subtropical regions. Comparisons with synoptic approaches demonstrated the additional information available within the dynamic TSI dataset that is lost in equivalent synoptic products derived from long-term monthly averages. The dynamic TSI dataset presented here provides a new product with far richer spatial and temporal information than any other presently available for Africa. As spatiotemporal malaria modeling endeavors evolve, dynamic predictor variables such as the malaria temperature suitability data developed here will be essential for the rational assessment of changing patterns of malaria risk.

Modeling Within-Host Effects of Drugs on Plasmodium falciparum Transmission and Prospects for Malaria Elimination

Abstract: Achieving a theoretical foundation for malaria elimination will require a detailed understanding of the quantitative relationships between patient treatment-seeking behavior, treatment coverage, and the effects of curative therapies that also block Plasmodium parasite transmission to mosquito vectors. Here, we report a mechanistic, within-host mathematical model that uses pharmacokinetic (PK) and pharmacodynamic (PD) data to simulate the effects of artemisinin-based combination therapies (ACTs) on Plasmodium falciparum transmission. To contextualize this model, we created a set of global maps of the fold reductions that would be necessary to reduce the malaria RC (i.e. its basic reproductive number under control) to below 1 and thus interrupt transmission. This modeling was applied to low-transmission settings, defined as having a R0<10 based on 2010 data. Our modeling predicts that treating 93–98% of symptomatic infections with an ACT within five days of fever onset would interrupt malaria transmission for ~91% of the at-risk population of Southeast Asia and ~74% of the global at-risk population, and lead these populations towards malaria elimination. This level of treatment coverage corresponds to an estimated 81–85% of all infected individuals in these settings. At this coverage level with ACTs, the addition of the gametocytocidal agent primaquine affords no major gains in transmission reduction. Indeed, we estimate that it would require switching ~180 people from ACTs to ACTs plus primaquine to achieve the same transmission reduction as switching a single individual from untreated to treated with ACTs. Our model thus predicts that the addition of gametocytocidal drugs to treatment regimens provides very small population-wide benefits and that the focus of control efforts in Southeast Asia should be on increasing prompt ACT coverage. Prospects for elimination in much of Sub-Saharan Africa appear far less favorable currently, due to high rates of infection and less frequent and less rapid treatment.

Declining malaria in Africa: improving the measurement of progress.

Abstract: The dramatic escalation of malaria control activities in Africa since the year 2000 has increased the importance of accurate measurements of impact on malaria epidemiology and burden. This study presents a systematic review of the emerging published evidence base on trends in malaria risk in Africa and argues that more systematic, timely, and empirically-based approaches are urgently needed to track the rapidly evolving landscape of transmission.

Diagnostic testing of pediatric fevers: meta-analysis of 13 national surveys assessing influences of malaria endemicity and source of care on test uptake for febrile children under five years.

Abstract: In 2010, the World Health Organization revised guidelines to recommend diagnosis of all suspected malaria cases prior to treatment. There has been no systematic assessment of malaria test uptake for pediatric fevers at the population level as countries start implementing guidelines. We examined test use for pediatric fevers in relation to malaria endemicity and treatment-seeking behavior in multiple sub-Saharan African countries in initial years of implementation. We compiled data from national population-based surveys reporting fever prevalence, care-seeking and diagnostic use for children under five years in 13 sub-Saharan African countries in 2009-2011/12 (n = 105,791). Mixed-effects logistic regression models quantified the influence of source of care and malaria endemicity on test use after adjusting for socioeconomic covariates. Results were stratified by malaria endemicity categories: low (PfPR2-10 40%). Among febrile under-fives surveyed, 16.9% (95% CI: 11.8%-21.9%) were tested. Compared to hospitals, febrile children attending non-hospital sources (OR: 0.62, 95% CI: 0.56-0.69) and community health workers (OR: 0.31, 95% CI: 0.23-0.43) were less often tested. Febrile children in high-risk areas had reduced odds of testing compared to low-risk settings (OR: 0.51, 95% CI: 0.42-0.62). Febrile children in least poor households were more often tested than in poorest (OR: 1.63, 95% CI: 1.39-1.91), as were children with better-educated mothers compared to least educated (OR: 1.33, 95% CI: 1.16-1.54). Diagnostic testing of pediatric fevers was low and inequitable at the outset of new guidelines. Greater testing is needed at lower or less formal sources where pediatric fevers are commonly managed, particularly to reach the poorest. Lower test uptake in high-risk settings merits further investigation given potential implications for diagnostic scale-up in these areas. Findings could inform continued implementation of new guidelines to improve access to and equity in point-of-care diagnostics use for pediatric fevers.

Defining the Geographical Range of the Plasmodiumknowlesi Reservoir

Abstract: Background: The simian malaria parasite, Plasmodium knowlesi, can cause severe and fatal disease in humans yet it is rarely included in routine public health reporting systems for malaria and its geographical range is largely unknown. Because malaria caused by P. knowlesi is a truly neglected tropical disease, there are substantial obstacles to defining the geographical extent and risk of this disease. Information is required on the occurrence of human cases in different locations, on which non-human primates host this parasite and on which vectors are able to transmit it to humans. We undertook a systematic review and ranked the existing evidence, at a subnational spatial scale, to investigate the potential geographical range of the parasite reservoir capable of infecting humans. Methodology/Principal Findings: After reviewing the published literature we identified potential host and vector species and ranked these based on how informative they are for the presence of an infectious parasite reservoir, based on current evidence. We collated spatial data on parasite occurrence and the ranges of the identified host and vector species. The ranked spatial data allowed us to assign an evidence score to 475 subnational areas in 19 countries and we present the results on a map of the Southeast and South Asia region. Conclusions/Significance: We have ranked subnational areas within the potential disease range according to evidence for presence of a disease risk to humans, providing geographical evidence to support decisions on prevention, management and prophylaxis. This work also highlights the unknown risk status of large parts of the region. Within this unknown category, our map identifies which areas have most evidence for the potential to support an infectious reservoir and are therefore a priority for further investigation. Furthermore we identify geographical areas where further investigation of putative host and vector species would be highly informative for the region-wide assessment.

Insecticide-treated nets (ITNs) in Africa 2000-2016: coverage, system efficiency and future needs for achieving international targets

Abstract: Insecticide-treated nets (ITNs), which comprise conventional (cITNs) and long-lasting insecticidal nets (LLINs), are the most widely used intervention for malaria control in Africa today. At least 700 million such nets have been financed and delivered to countries since the onset of the Roll Back Malaria (RBM) partnership at the turn of the millennium, but coverage remains inadequate. Better understanding of how and why these volumes of net deliveries translate into the levels of access and use seen in households across Africa could improve the monitoring of coverage indicators, highlight opportunities for systematic efficiency gains, and allow more accurate assessment of resources needed to meet international targets. We used a simple compartmental model to represent the system linking ITN deliveries to countries, distribution to households, and resulting coverage at the national level. We assembled coverage data from 93 national surveys representing 861,000 households between 2000 and 2013 and triangulated these against yearly ITN manufacturer delivery data and national malaria control programme ITN distribution reports for 44 sub-Saharan countries. We fitted the model to these data using Bayesian inference with minimal prior assumptions. We present contemporary estimates of LLIN coverage for all endemic African countries since the year 2000. We then explore the impact of two potential inefficiencies: uneven net distribution between households and rapid rates of net loss from households. These factors substantially reduce the levels of coverage achieved relative to the volume of LLINs financed and delivered, but are not fully captured in current approaches to calculating LLIN needs. Using these inferences, we estimate the levels of coverage achievable with differing volumes of LLIN provision by 2016 under various scenarios of current or modified future levels of distributional efficiency and retention by households. Despite dramatic gains, current levels of ITN access and use remain well below international targets. Unless inefficiencies due to uneven distribution and rapid net loss can be addressed, meeting international targets will require substantially more nets than currently assumed.

Risk factors for UK Plasmodium falciparum cases

Abstract: Background An increasing proportion of malaria cases diagnosed in UK residents with a history of travel to malaria endemic areas are due to Plasmodium falciparum.

Comparing community P. falciparum infection prevalence measured via microscopy versus rapid diagnostic test

Abstract: Large scale mapping of Plasmodium falciparum infection prevalence, such as that undertaken by the Malaria Atlas Project, relies on opportunistic assemblies of data on infection prevalence arising from thousands of P. falciparum parasite rate (PfPR) surveys conducted worldwide. Variance in these data is driven by both signal - the true underlying pattern of infection prevalence - and a range of factors contributing to ‘noise’ - including sampling error, differing age ranges of subjects, and differing parasite detection methods. Whilst the former two have been addressed in previous maps, the effect of different diagnostic methods used to determine PfPR in different studies has not. In particular, the majority of PfPR data are based on positivity rates determined by either microscopy or rapid diagnostic test (RDT), and it is known that the sensitivity and specificity of these approaches are not equivalent. There is therefore a need for a method to quantitatively compare and adjust RDT- and microscopy-based prevalence estimates to a common standard prior to use in mapping. Here we estimate a relationship between RDT- and microscopy-derived PfPR using paired RDT and microscopy outcomes from sub-Saharan African populations. A total of 19 Demographic and Health Survey datasets from sub-Saharan Africa provide child diagnostic test results derived using both RDT and microscopy for each individual. We aggregated these prevalence estimates across administration zones (ADMIN1) and fitted a Bayesian probit regression to the microscopy- versus RDT-derived prevalence relationship. We employed an errors-in-variables approach to acknowledge sampling error in both the dependent and independent variable. In addition to the diagnostic outcome, several factors were extracted from the datasets in order to analyze their effect on observed malaria prevalence, sensitivity and specificity. These factors included: RDT type, fever status, recent ACT treatment, and estimated local population malaria prevalence. We present results of stratified regression and analysis of variance analyses to establish the influence of these factors on measured prevalence, sensitivity and specificity. The fitted models can be applied to RDT-derived PfPR data to convert them to an estimate of the prevalence expected using microscopy, thereby standardizing the dataset and improving the signal-to-noise ratio. Additionally, our results provide insight into factors that influence the observed prevalence, sensitivity and specificity of different diagnostic techniques.