Modeling of the dynamics of paludism in Madagascar

D'après le rapport de l'OMS en 2015, près de la moitié de la population mondiale est exposée au risque du paludisme et le plus grand nombre des cas recensés se trouve en Afrique subsaharienne. Madagascar fait partie des pays où le paludisme est encore endémique. La géographie et le climat de l'île se traduisent par une répartition assez particulière du paludisme. Les plus fortes incidences sont observées sur les littoraux alors que les plus faibles le sont sur les Hautes Terres Centrales. Cinq zones épidémiologiques et opérationnelles ont été définies par les services de lutte contre le paludisme : Est, Ouest, Sud, Hautes Terres et les Marges. Cette étude vise à apporter une meilleure compréhension de l'épidémiologie du paludisme et de mesurer l'impact des mobilités humaines sur la transmission des zones à forte transmission vers les zones à faible transmission afin de contribuer à mieux cibler les actions de contrôle par les acteurs de la santé publique. Elle offre une nouvelle approche permettant d'évaluer la dynamique spatio-temporelle du paludisme, de quantifier la circulation de l'infection palustre en tenant compte de la mobilité de la population par l’utilisation des données de téléphonie mobile et d'identifier les principales zones exportatrices et importatrices de la maladie. En premier lieu, à travers une analyse rétrospective des données d'incidence, ce travail a montré une hétérogénéité évidente dans chaque stratification épidémiologique et la recrudescence de la maladie sur les Hautes Terres et les Marges. En second lieu, indépendamment de la densité de la population, nous avons montré que les Hautes Terres et surtout la capitale Antananarivo sont une zone à fort risque d'importation de paludisme et que les zones exportatrices sont surtout situées à l'Est et à l'Ouest. Enfin, notre enquête de terrain a souligné l'importance d'une mobilité inter district faible et d'une mobilité intra district voire intra communale importante qui mériterait d'être prise en compte dans la mesure de la circulation de l'infection palustre. Cette étude a permis de mettre en lumière que le paludisme est très dynamique à Madagascar avec un degré d'intensité différent même si les zones appartiennent à la même stratification. Ce constat devrait se traduire par une adaptation des stratégies de lutte. Enfin, la mobilité humaine joue un rôle important dans la transmission. A l'heure où la téléphonie mobile s'est largement diffusée à Madagascar, son utilisation pour estimer le déplacement des populations devient un outil pertinent pour contribuer à orienter le contrôle des maladies.According to the 2015 WHO report, almost half of the world population is exposed to malaria, with the largest number of reported cases in sub-Saharan Africa. Madagascar is one of the countries where malaria is still endemic because of its geographical location. As a matter of fact, the geography and climate of the island gives a specific epidemiological stratification of malaria. There are five malaria epidemiological zones: East, West, South, Highlands and Fringe. The highest incidence is observed on coastal areas, while the lowest incidence is observed on the Central Highlands. This study aims to provide a better understanding of the epidemiology of malaria and to measure the impact of human mobility on transmission from high transmission areas to low transmission areas in order to help better target control actions by public health actors. This study proposes an alternative approach to assess the spatiotemporal dynamics of malaria, quantify the circulation of malaria infection and take into account the mobility of the population to identify the main source and sink areas of malaria. Firstly, through a retrospective analysis of incidence data, this work showed a clear heterogeneity in each stratum, and an increase the Highlands and the Fringe areas. Secondly, regardless of the population density, we have shown that the Highlands and especially the capital of Madagascar, Antananarivo, was a zone at high risk of the importation of malaria. The source areas were mainly in the eastern and the western part of the country. Finally, our field survey highlighted the importance of low inter-district mobility and high intra-district or even intra-communal mobility which should be taken into consideration when assessing the spreading of malaria infection. This study revealed that malaria is very dynamic in Madagascar with a different degree of intensity even if such areas belong to the same stratum. This observation should translate into an adaptation of control strategies. Finally, human mobility plays a leading part in the transmission. At a time when mobile telephony has spread widely in Madagascar, its use to estimate the mobility of populations is becoming a relevant tool to help guide disease control

Modélisation de la dynamique du paludisme à Madagascar

According to the 2015 WHO report, almost half of the world population is exposed to malaria, with the largest number of reported cases in sub-Saharan Africa. Madagascar is one of the countries where malaria is still endemic because of its geographical location. As a matter of fact, the geography and climate of the island gives a specific epidemiological stratification of malaria. There are five malaria epidemiological zones: East, West, South, Highlands and Fringe. The highest incidence is observed on coastal areas, while the lowest incidence is observed on the Central Highlands. This study aims to provide a better understanding of the epidemiology of malaria and to measure the impact of human mobility on transmission from high transmission areas to low transmission areas in order to help better target control actions by public health actors. This study proposes an alternative approach to assess the spatiotemporal dynamics of malaria, quantify the circulation of malaria infection and take into account the mobility of the population to identify the main source and sink areas of malaria. Firstly, through a retrospective analysis of incidence data, this work showed a clear heterogeneity in each stratum, and an increase the Highlands and the Fringe areas. Secondly, regardless of the population density, we have shown that the Highlands and especially the capital of Madagascar, Antananarivo, was a zone at high risk of the importation of malaria. The source areas were mainly in the eastern and the western part of the country. Finally, our field survey highlighted the importance of low inter-district mobility and high intra-district or even intra-communal mobility which should be taken into consideration when assessing the spreading of malaria infection. This study revealed that malaria is very dynamic in Madagascar with a different degree of intensity even if such areas belong to the same stratum. This observation should translate into an adaptation of control strategies. Finally, human mobility plays a leading part in the transmission. At a time when mobile telephony has spread widely in Madagascar, its use to estimate the mobility of populations is becoming a relevant tool to help guide disease control.D'après le rapport de l'OMS en 2015, près de la moitié de la population mondiale est exposée au risque du paludisme et le plus grand nombre des cas recensés se trouve en Afrique subsaharienne. Madagascar fait partie des pays où le paludisme est encore endémique. La géographie et le climat de l'île se traduisent par une répartition assez particulière du paludisme. Les plus fortes incidences sont observées sur les littoraux alors que les plus faibles le sont sur les Hautes Terres Centrales. Cinq zones épidémiologiques et opérationnelles ont été définies par les services de lutte contre le paludisme : Est, Ouest, Sud, Hautes Terres et les Marges. Cette étude vise à apporter une meilleure compréhension de l'épidémiologie du paludisme et de mesurer l'impact des mobilités humaines sur la transmission des zones à forte transmission vers les zones à faible transmission afin de contribuer à mieux cibler les actions de contrôle par les acteurs de la santé publique. Elle offre une nouvelle approche permettant d'évaluer la dynamique spatio-temporelle du paludisme, de quantifier la circulation de l'infection palustre en tenant compte de la mobilité de la population par l’utilisation des données de téléphonie mobile et d'identifier les principales zones exportatrices et importatrices de la maladie. En premier lieu, à travers une analyse rétrospective des données d'incidence, ce travail a montré une hétérogénéité évidente dans chaque stratification épidémiologique et la recrudescence de la maladie sur les Hautes Terres et les Marges. En second lieu, indépendamment de la densité de la population, nous avons montré que les Hautes Terres et surtout la capitale Antananarivo sont une zone à fort risque d'importation de paludisme et que les zones exportatrices sont surtout situées à l'Est et à l'Ouest. Enfin, notre enquête de terrain a souligné l'importance d'une mobilité inter district faible et d'une mobilité intra district voire intra communale importante qui mériterait d'être prise en compte dans la mesure de la circulation de l'infection palustre. Cette étude a permis de mettre en lumière que le paludisme est très dynamique à Madagascar avec un degré d'intensité différent même si les zones appartiennent à la même stratification. Ce constat devrait se traduire par une adaptation des stratégies de lutte. Enfin, la mobilité humaine joue un rôle important dans la transmission. A l'heure où la téléphonie mobile s'est largement diffusée à Madagascar, son utilisation pour estimer le déplacement des populations devient un outil pertinent pour contribuer à orienter le contrôle des maladies

Mapping on OpenStreetMap to improve access to health care in a rural district of Madagascar

International audienc

Epidemiology of malaria in Madagascar : spatio-temporal distribution of complicated and uncomplicated malaria

International audienceMalaria is endemic in Madagascar and a leading cause of mortality and morbidity. Its geographical distribution is heterogeneous throughout the country, in relation to climatic, environmental and social factors. In this study, we analyze the spatiotemporal distribution of malaria caused by Plasmodium falciparum.The Service for Health and Demographic Statistics of the Ministry of Public Health provided monthly epidemiological data related to complicated and uncomplicated malaria cases from 2010 to 2014. We analyzed and integrated these data into a Geographic Information System to map malaria trends by year, by month and by age for each district. The incidence of malaria has increased since 2012 and remains high in some coastal districts. The highest peaks of reported cases are observed between January and April with especially high incidences along the Eastern coast. The average of uncomplicated malaria cases of children less than five years represent about 36% of cases for each year. Both complicated and uncomplicated malaria show similar patterns and trends.The quality of epidemiological data is discussed regarding the provision and access to health services. The connectivity between districts and the persistence of malaria on the coast could induce the emergence of malaria in central highlands following reintroduction by travelers. Thus, non-endemic areas are at risk of emergence with complicated clinical malaria form. Districts presenting significantly high incidences should be carefully monitored in order to reduce transmission

Spatial and temporal dynamics of malaria in Madagascar

International audienceBackground: Malaria 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 zone were studied. Methods: The 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. Results: The 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. Conclusion: This 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

Geographic barriers to achieving universal health coverage: evidence from rural Madagascar

International audiencePoor geographic access can persist even when affordable and well-functioning health systems are in place, limiting efforts for universal health coverage (UHC). It is unclear how to balance support for health facilities and community health workers in UHC national strategies. The goal of this study was to evaluate how a health system strengthening (HSS) intervention aimed towards UHC affected the geographic access to primary care in a rural district of Madagascar. For this, we collected the fokontany of residence (lowest administrative unit) from nearly 300 000 outpatient consultations occurring in facilities of Ifanadiana district in 2014-2017 and in the subset of community sites supported by the HSS intervention. Distance from patients to facilities was accurately estimated following a full mapping of the district's footpaths and residential areas. We modelled per capita utilization for each fokontany through interrupted time-series analyses with control groups, accounting for nonlinear relationships with distance and travel time among other factors, and we predicted facility utilization across the district under a scenario with and without HSS. Finally, we compared geographic trends in primary care when combining utilization at health facilities and community sites. We find that facility-based interventions similar to those in UHC strategies achieved high utilization rates of 1-3 consultations per person year only among populations living in close proximity to facilities. We predict that scaling only facility-based HSS programmes would result in large gaps in access, with over 75% of the population unable to reach one consultation per person year. Community health delivery, available only for children under 5 years, provided major improvements in service utilization regardless of their distance from facilities, contributing to 90% of primary care consultations in remote populations. Our results reveal the geographic limits of current UHC strategies and highlight the need to invest on professionalized community health programmes with larger scopes of service

Estimating the local spatio‐temporal distribution of malaria from routine health information systems in areas of low health care access and reporting

International audienceBackground: Reliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care. Methods: We use a geographically explicit dataset with residences of the 73,022 malaria cases confirmed at health centers in the Ifanadiana District in Madagascar from 2014 to 2017. Malaria incidence was adjusted to account for underreporting due to stock-outs of rapid diagnostic tests and variable access to healthcare. A benchmark multiplier was combined with a health care utilization index obtained from statistical models of non-malaria patients. Variations to the multiplier and several strategies for pooling neighboring communities together were explored to allow for fine-tuning of the final estimates. Separate analyses were carried out for individuals of all ages and for children under five. Cross-validation criteria were developed based on overall incidence, trends in financial and geographical access to health care, and consistency with geographic distribution in a district-representative cohort. The most plausible sets of estimates were then identified based on these criteria. Results: Passive surveillance was estimated to have missed about 4 in every 5 malaria cases among all individuals and 2 out of every 3 cases among children under five. Adjusted malaria estimates were less biased by differences in populations’ financial and geographic access to care. Average adjusted monthly malaria incidence was nearly four times higher during the high transmission season than during the low transmission season. By gathering patient-level data and removing systematic biases in the dataset, the spatial resolution of passive malaria surveillance was improved over ten-fold. Geographic distribution in the adjusted dataset revealed high transmission clusters in low elevation areas in the northeast and southeast of the district that were stable across seasons and transmission years. Conclusions: Understanding local disease dynamics from routine passive surveillance data can be a key step towards achieving universal access to diagnostics and treatment. Methods presented here could be scaled-up thanks to the increasing availability of e-health disease surveillance platforms for malaria and other diseases across the developing world

Spatiotemporal epidemiology of malaria in Madagascar between 2006 and 2015

International audienceBackground: Malaria is endemic in Madagascar, with local specificities. Its transmission occurs throughout the year along the eastern coast, while it is unstable and seasonal on Central High- lands. In this study, we investigate the spatiotemporal patterns of the occurrence of malaria in relation to bioclimatic conditions.Methods & Materials: The Service for Health and Demographic Statistics of the Ministry of Public Health provided epidemio- logical data related to complicated and uncomplicated malaria cases from 2006 to April 2015. We integrated these data into a Geographic Information System to map monthly incidence for each health district and identify spatiotemporal clusters. We also acquired environmental information (meteorological and vegeta- tion indices) in order to assess relations with malaria incidences.Results: Since 2010, the report of malaria cases has improved and malaria incidence shows more regular trends. Malaria trans- mission generally starts with the rainy season and has a distinct peak on February and March. Children under 15 years old are the most vulnerable over the country. Coastal districts can be considered as a source of malaria because of their high incidence all over the year.Conclusion: The quality of epidemiological data is discussed regarding the provision and access to health services. Case reports show weaknesses for some remote areas and at the end of each year. The persistence of malaria on the coast could induce the emer- gence of malaria in Central Highlands following reintroduction by travelers

Estimating sources and sinks of malaria parasites in Madagascar

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

Geographic barriers to care persist at the community healthcare level: Evidence from rural Madagascar

International audienceGeographic distance is a critical barrier to healthcare access, particularly for rural communities with poor transportation infrastructure who rely on non-motorized transportation. There is broad consensus on the importance of community health workers (CHWs) to reduce the effects of geographic isolation on healthcare access. Due to a lack of fine-scale spatial data and individual patient records, little is known about the precise effects of CHWs on removing geographic barriers at this level of the healthcare system. Relying on a high-quality, crowdsourced dataset that includes all paths and buildings in the area, we explored the impact of geographic distance from CHWs on the use of CHW services for children under 5 years in the rural district of Ifanadiana, southeastern Madagascar from 2018-2021. We then used this analysis to determine key features of an optimal geographic design of the CHW system, specifically optimizing a single CHW location or installing additional CHW sites. We found that consultation rates by CHWs decreased with increasing distance patients travel to the CHW by approximately 28.1% per km. The optimization exercise revealed that the majority of CHW sites (50/80) were already in an optimal location or shared an optimal location with a primary health clinic. Relocating the remaining CHW sites based on a geographic optimum was predicted to increase consultation rates by only 7.4%. On the other hand, adding a second CHW site was predicted to increase consultation rates by 31.5%, with a larger effect in more geographically dispersed catchments. Geographic distance remains a barrier at the level of the CHW, but optimizing CHW site location based on geography alone will not result in large gains in consultation rates. Rather, alternative strategies, such as the creation of additional CHW sites or the implementation of proactive care, should be considered