Vincent Herbreteau

Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network: a web-based application

BackgroundThe use of a malaria early warning system (MEWS) to trigger prompt public health interventions is a key step in adding value to the epidemiological data routinely collected by sentinel surveillance systems.MethodsThis study describes a system using various epidemic thresholds and a forecasting component with the support of new technologies to improve the performance of a sentinel MEWS. Malaria-related data from 21 sentinel sites collected by Short Message Service are automatically analysed to detect malaria trends and malaria outbreak alerts with automated feedback reports.ResultsRoll Back Malaria partners can, through a user-friendly web-based tool, visualize potential outbreaks and generate a forecasting model. The system already demonstrated its ability to detect malaria outbreaks in Madagascar in 2014.ConclusionThis approach aims to maximize the usefulness of a sentinel surveillance system to predict and detect epidemics in limited-resource environments.

Spatial and temporal dynamics of malaria in Madagascar

BackgroundMalaria is one of the primary health concerns in Madagascar. Based on the duration and intensity of transmission, Madagascar is divided into five epidemiological strata that range from low to mesoendemic transmission. In this study, the spatial and temporal dynamics of malaria within each epidemiological zonexa0were studied.MethodsThe number of reported cases of uncomplicated malaria from 112 health districts between 2010 and 2014 were compiled and analysed. First, a Standardized Incidence Ratio was calculated to detect districts with anomalous incidence compared to the stratum-level incidence. Building on this, spatial and temporal malaria clusters were identified throughout the country and their variability across zones and over time was analysed.ResultsThe incidence of malaria increased from 2010 to 2014 within each stratum. A basic analysis showed that districts with more than 50 cases per 1000 inhabitants are mainly located in two strata: East and West. Lower incidence values were found in the Highlands and Fringe zones. The standardization method revealed that the number of districts with a higher than expected numbers of cases increased through time and expanded into the Highlands and Fringe zones. The cluster analysis showed that for the endemic coastal region, clusters of districts migrated southward and the incidence of malaria was the highest between January and July with some variation within strata.ConclusionThis study identified critical districts with low incidence that shifted to high incidence and district that were consistent clusters across each year. The current study provided a detailed description of changes in malaria epidemiology and can aid the national malaria programme to reduce and prevent the expansion of the disease by targeting the appropriate areas.

Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing

The prevention and control of mosquito-borne diseases, such as malaria, are important health issues in tropical areas. Malaria transmission is a multi-scale process strongly controlled by environmental factors, and the use of remote-sensing data is suitable for the characterization of its spatial and temporal dynamics. Synthetic aperture radar (SAR) is well-adapted to tropical areas, since it is capable of imaging independent of light and weather conditions. In this study, we highlight the contribution of SAR sensors in the assessment of the relationship between vectors, malaria and the environment in the Amazon region. More specifically, we focus on the SAR-based characterization of potential breeding sites of mosquito larvae, such as man-made water collections and natural wetlands, providing guidelines for the use of SAR capabilities and techniques in order to optimize vector control and malaria surveillance. In light of these guidelines, we propose a framework for the production of spatialized indicators and malaria risk maps based on the combination of SAR, entomological and epidemiological data to support malaria risk prevention and control actions in the field.

Evaluating Effectiveness of Mass and Continuous Long-lasting Insecticidal Net Distributions Over Time in Madagascar: A Sentinel Surveillance Based Epidemiological Study

Background The reduction of global malaria burden over the past 15u202fyears is much attributed to the expansion of mass distribution campaigns (MDCs) of long-lasting insecticidal nets (LLIN). In Madagascar, two LLIN MDCs were implemented and one district also benefited from a community-based continuous distribution (CB-CD). Malaria incidence dropped but eventually rebounded after a decade. Methods Data from a sentinel surveillance network over the 2009–2015 period was analyzed. Alerts were defined as weekly number of malaria cases exceeding the 90th percentile value for three consecutive weeks. Statistical analyses assessed the temporal relationship between LLIN MDCs and (i) number of malaria cases and (ii) malaria alerts detected, and (iii) the effect of a combination of MDCs and a CB-CD in Toamasina District. Findings Analyses showed an increase of 13.6 points and 21.4 points in the percentile value of weekly malaria cases during the second and the third year following the MDC of LLINs respectively. The percentage of alert-free sentinel sites was 98.2% during the first year after LLIN MDC, 56.7% during the second year and 31.5% during the third year. The number of weekly malaria cases decreased by 14% during the CB-CD in Toamasina District. In contrast, sites without continuous distribution had a 12% increase of malaria cases. Interpretation These findings support the malaria-preventive effectiveness of MDCs in Madagascar but highlight their limited duration when not followed by continuous distribution. The resulting policy implications are crucial to sustain reductions in malaria burden in high transmission settings.

Estimating sources and sinks of malaria parasites in Madagascar

In areas where malaria epidemiology is spatially and temporally heterogeneous, human-mediated parasite importation can result in non-locally acquired clinical cases and outbreaks in low-transmission areas. Using mobility estimates derived from the mobile phone data and spatial malaria prevalence data, we identify travel routes relevant to malaria transmission in Madagascar. We find that the primary hubs of parasite importation are in a spatially connected area of the central highlands. Surprisingly, sources of these imported infections are not spatially clustered. We then related these source locations directly to clinical cases in the low-transmission area of the capital. We find that in the capital, a major sink, the primary sources of infection are along the more populated coastal areas, although these sources are seasonally variable. Our results have implications for targeting interventions at source locations to achieve local or national malaria control goals.Understanding the source of malaria outbreaks in low-transmission areas is important for controlling the disease. Here, the authors use mobile phone data to map malaria transmission in Madagascar, and are able to show that primary sources of infection in the capital city are found along populated coastal areas.

Spatio-temporal dynamic of malaria in Ouagadougou, Burkina Faso, 2011–2015

BackgroundGiven the scarcity of resources in developing countries, malaria treatment requires new strategies that target specific populations, time periods and geographical areas. While the spatial pattern of malaria transmission is known to vary depending on local conditions, its temporal evolution has yet to be evaluated. The aim of this study was to determine the spatio-temporal dynamic of malaria in the central region of Burkina Faso, taking into account meteorological factors.MethodsDrawing on national databases, 101 health areas were studied from 2011 to 2015, together with weekly meteorological data (temperature, number of rain events, rainfall, humidity, wind speed). Meteorological factors were investigated using a principal component analysis (PCA) to reduce dimensions and avoid collinearities. The Box–Jenkins ARIMA model was used to test the stationarity of the time series. The impact of meteorological factors on malaria incidence was measured with a general additive model. A change-point analysis was performed to detect malaria transmission periods. For each transmission period, malaria incidence was mapped and hotspots were identified using spatial cluster detection.ResultsMalaria incidence never went below 13.7 cases/10,000 person-weeks. The first and second PCA components (constituted by rain/humidity and temperatures, respectively) were correlated with malaria incidence with a lag of 2xa0weeks. The impact of temperature was significantly non-linear: malaria incidence increased with temperature but declined sharply with high temperature. A significant positive linear trend was found for the entire time period. Three transmission periods were detected: low (16.8–29.9 cases/10,000 person-weeks), high (51.7–84.8xa0cases/10,000xa0person-weeks), and intermediate (26.7–32.2xa0cases/10,000xa0person-weeks). The location of clusters identified as high risk varied little across transmission periods.ConclusionThis study highlighted the spatial variability and relative temporal stability of malaria incidence around the capital Ouagadougou, in the central region of Burkina Faso. Despite increasing efforts in fighting the disease, malaria incidence remained high and increased over the period of study. Hotspots, particularly those detected for low transmission periods, should be investigated further to uncover the local environmental and behavioural factors of transmission, and hence to allow for the development of better targeted control strategies.

Applications of Remote Sensing to the Epidemiology of Infectious Diseases: Some Examples

Infectious diseases are caused by a pathogenic microorganism (virus, bacterium, parasite or fungus) and have a significant impact on public and animal health. In public health, they are one of the leading causes of death and are priorities in the poorest countries. In animal health, they can be devastating and radical measures are taken to prevent them from spreading. Infectious diseases therefore have major economic consequences, in terms of both healthcare and livestock production losses. In recent decades, we have seen the emergence of a significant number of infectious diseases, such as chikungunya, avian influenza and Ebola. These diseases have spread around the world all the more dramatically due to the rapid movement of populations and goods. The majority of pathogenic agents responsible for these emergences are zoonotic (transmitted from animals to humans or vice versa). There has also been a significant increase in vector-borne diseases – that is diseases whose pathogenic agent is transmitted through the intermediary of a vector. Vectors are arthropods (e.g. mosquitoes, fleas, sand flies and reduviid bugs) and acarids (e.g. ticks). One example is the mosquito Aedes albopictus, more commonly known as the “tiger mosquito”, which is a vector for the chikungunya and dengue viruses. The geographical distribution of this mosquito is increasing year by year. This species was responsible for the first indigenous cases of chikungunya in France in 2010.