Spatio-temporal analysis and prediction of malaria cases using remote sensing meteorological data in Diébougou health district, Burkina Faso, 2016–2017

International audienceMalaria control and prevention programs are more efficient and cost-effective when they target hotspots or select the best periods of year to implement interventions. This study aimed to identify the spatial distribution of malaria hotspots at the village level in Diébougou health district, Burkina Faso, and to model the temporal dynamics of malaria cases as a function of meteorological conditions and of the distance between villages and health centres (HCs). Case data for 27 villages were collected in 13 HCs. Meteorological data were obtained through remote sensing. Two synthetic meteorological indicators (SMIs) were created to summarize meteorological variables. Spatial hotspots were detected using the Kulldorf scanning method. A General Additive Model was used to determine the time lag between cases and SMIs and to evaluate the effect of SMIs and distance to HC on the temporal evolution of malaria cases. The multivariate model was fitted with data from the epidemic year to predict the number of cases in the following outbreak. Overall, the incidence rate in the area was 429.13 cases per 1000 person-year with important spatial and temporal heterogeneities. Four spatial hotspots, involving 7 of the 27 villages, were detected, for an incidence rate of 854.02 cases per 1000 person-year. The hotspot with the highest risk (relative risk = 4.06) consisted of a single village, with an incidence rate of 1750.75 cases per 1000 person-years. The multivariate analysis found greater variability in incidence between HCs than between villages linked to the same HC. The time lag that generated the better predictions of cases was 9 weeks for SMI1 (positively correlated with precipitation variables) and 16 weeks for SMI2 (positively correlated with temperature variables. The prediction followed the overall pattern of the time series of reported cases and predicted the onset of the following outbreak with a precision of less than 3 weeks. This analysis of malaria cases in Diébougou health district, Burkina Faso, provides a powerful prospective method for identifying and predicting high-risk areas and high-transmission periods that could be targeted in future malaria control and prevention campaigns

Malaria in Burkina Faso: A comprehensive analysis of spatiotemporal distribution of incidence and environmental drivers, and implications for control strategies

International audienceBackground The number of malaria cases worldwide has increased, with over 241 million cases and 69,000 more deaths in 2020 compared to 2019. Burkina Faso recorded over 11 million malaria cases in 2020, resulting in nearly 4,000 deaths. The overall incidence of malaria in Burkina Faso has been steadily increasing since 2016. This study investigates the spatiotemporal pattern and environmental and meteorological determinants of malaria incidence in Burkina Faso. Methods We described the temporal dynamics of malaria cases by detecting the transmission periods and the evolution trend from 2013 to 2018. We detected hotspots using spatial scan statistics. We assessed different environmental zones through a hierarchical clustering and analyzed the environmental and climatic data to identify their association with malaria incidence at the national and at the district’s levels through generalized additive models. We also assessed the time lag between malaria peaks onset and the rainfall at the district level. The environmental and climatic data were synthetized into indicators. Results The study found that malaria incidence had a seasonal pattern, with high transmission occurring during the rainy seasons. We also found an increasing trend in the incidence. The highest-risk districts for malaria incidence were identified, with a significant expansion of high-risk areas from less than half of the districts in 2013–2014 to nearly 90% of the districts in 2017–2018. We identified three classes of health districts based on environmental and climatic data, with the northern, south-western, and western districts forming separate clusters. Additionally, we found that the time lag between malaria peaks onset and the rainfall at the district level varied from 7 weeks to 17 weeks with a median at 10 weeks. Environmental and climatic factors have been found to be associated with the number of cases both at global and districts levels. Conclusion The study provides important insights into the environmental and spatiotemporal patterns of malaria in Burkina Faso by assessing the spatio temporal dynamics of Malaria cases but also linking those dynamics to the environmental and climatic factors. The findings highlight the importance of targeted control strategies to reduce the burden of malaria in high-risk areas as we found that Malaria epidemiology is complex and linked to many factors that make some regions more at risk than others

A transition support system to build decarbonization scenarios in the academic community

International audienceA growing portion of scientists realises the need to not only alert about climate change, but also change their professional practices. A range of tools have emerged to promote more sustainable activities, yet many scientists struggle to go beyond simple awareness-raising to create concrete transition actions. Here we propose a game-based transition support system MaTerre180’ , which has been designed to build scenarios of greenhouse gas (GHG) emission reductions in the academic community. After providing a common scientific background about the context (global warming issue, its causes and consequences) and setting up a challenge (50% reduction of carbon budget by 2030), the participants belonging to the academic community and its governance bodies immerse themselves into fictional characters, to simulate the behaviour of real research groups. The game has been deployed during the year 2021, with six hundred participants from nine countries and 50 cities. Results explore clear pathways for GHG reductions between 25 and 60%, and a median reduction of 46%. The alternatives allowing the greatest reduction are video communication tools (36%), followed by mutualization of professional activities and voluntary cancellation or reduction, that represent 22 and 14% of reduction, respectively. The remaining 28% of reduction consists of transport alternative, relocation of professional activities, extended duration of some travels, etc. In addition, the analyses pointed out the importance of the guided negotiation phase to bring out some alternatives such as relocation, local partners and computing optimization. An added value of this transition support system is that the information it collects (anonymously) will be used to answer pressing research questions in climate change science and environmental psychology regarding the use of serious games for promoting changes in attitudes and behaviours towards sustainability, and including broader questions on how network structures influence “climate behaviour”, knowledge and the governance of the commons. Modestly, MaTerre180’ offers an innovative game-based transition support system to build scenarios of greenhouse gas (GHG) emission reductions in the academic community. It is not simply a question of moving tokens on a virtual gameboard and a playful adjustment of practices, but rather a question of brainstorming about possible and desirable ways of remodelling research and teaching communities and embracing a new paradigm. After tens of workshops, our results show clear pathways for reaching up to 50% GHG reductions and stress the importance of guided negotiations to bring out alternatives to carbonized activities. This first attempt reinforces our belief that scientific engagement is at the heart of the international development agenda and a key approach to tear down the institutional barriers that inhibit the transformation needed to achieve a more sustainable society