Seasonal Patterns of Mpox Index Cases, Africa, 1970-2021.

Across 133 confirmed mpox zoonotic index cases reported during 1970-2021 in Africa, cases occurred year-round near the equator, where climate is consistent. However, in tropical regions of the northern hemisphere under a dry/wet season cycle, cases occurred seasonally. Our findings further support the seasonality of mpox zoonotic transmission risk.

Understanding the impact of mobility on Plasmodium spp. carriage in an Amazon cross-border area with low transmission rate.

Despite the large reduction in malaria incidence in the last decade, the last kilometre to elimination is often the hardest, especially in international border areas. This study investigated the impact of mobility on Plasmodium spp. carriage in people living in a cross-border area in Amazonia with a low malaria transmission rate. We implemented a longitudinal ancillary study in the French Guiana town of St. Georges de l'Oyapock, which is located on the border with Brazil. It was based on data from two transversal surveys performed in October 2017 and October 2018. Data were collected on peri-domestic mobility for food-producing activities, and longer-distance mobility in high-risk areas. Participants were screened for Plasmodium spp. carriage using PCR tests, and treated if positive. Vector density around a participant's home was estimated using a previously published model based on remote sensing and meteorological data. The association between Plasmodium spp. carriage and mobility was analysed using a generalized additive mixed model. A total of 1,192 inhabitants, aged between 0 and 92 years old, were included. Median age was 18 years in 2017 (IQR [8;35]). Plasmodium spp. prevalence in the study population was 7% in 2017 (n = 89) and 3% in 2018 (n = 35). Plasmodium spp. carriage was independently associated with i) travel to the adjoining Oiapoque Indigenous Territories in Brazil (OR = 1.76, p = 0.023), ii) the estimated vector density around a participant's home (High versus Low risk OR = 4.11, p<0.001), iii) slash-and-burn farming (OR = 1.96, p = 0.013), and iv) age (p = 0.032). Specific surveillance systems and interventions which take into account different types of mobility are needed in cross-border areas to achieve and maintain malaria elimination (e.g., reactive case detection and treatment in the places visited).

'Forest malaria' in Myanmar? Tracking transmission landscapes in a diversity of environments.

BACKGROUND: In the Greater Mekong Subregion, case-control studies and national-level analyses have shown an association between malaria transmission and forest activities. The term 'forest malaria' hides the diversity of ecosystems in the GMS, which likely do not share a uniform malaria risk. To reach malaria elimination goals, it is crucial to document accurately (both spatially and temporally) the influence of environmental factors on malaria to improve resource allocation and policy planning within given areas. The aim of this ecological study is to characterize the association between malaria dynamics and detailed ecological environments determined at village level over a period of several years in Kayin State, Myanmar. METHODS: We characterized malaria incidence profiles at village scale based on intra- and inter-annual variations in amplitude, seasonality, and trend over 4 years (2016-2020). Environment was described independently of village localization by overlaying a 2-km hexagonal grid over the region. Specifically, hierarchical classification on principal components, using remote sensing data of high spatial resolution, was used to assign a landscape and a climate type to each grid cell. We used conditional inference trees and random forests to study the association between the malaria incidence profile of each village, climate and landscape. Finally, we constructed eco-epidemiological zones to stratify and map malaria risk in the region by summarizing incidence and environment association information. RESULTS: We identified a high diversity of landscapes (n = 19) corresponding to a gradient from pristine to highly anthropogenically modified landscapes. Within this diversity of landscapes, only three were associated with malaria-affected profiles. These landscapes were composed of a mosaic of dense and sparse forest fragmented by small agricultural patches. A single climate with moderate rainfall and a temperature range suitable for mosquito presence was also associated with malaria-affected profiles. Based on these environmental associations, we identified three eco-epidemiological zones marked by later persistence of Plasmodium falciparum, high Plasmodium vivax incidence after 2018, or a seasonality pattern in the rainy season. CONCLUSIONS: The term forest malaria covers a multitude of contexts of malaria persistence, dynamics and populations at risk. Intervention planning and surveillance could benefit from consideration of the diversity of landscapes to focus on those specifically associated with malaria transmission.

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

BACKGROUND: 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.

Geo-epidemiology of malaria incidence in the Vhembe District to guide targeted elimination strategies, South-Africa, 2015-2018: a local resurgence.

In South Africa, the population at risk of malaria is 10% (around six million inhabitants) and concern only three provinces of which Limpopo Province is the most affected, particularly in Vhembe District. As the elimination approaches, a finer scale analysis is needed to accelerate the results. Therefore, in the process of refining local malaria control and elimination strategies, the aim of this study was to identify and describe malaria incidence patterns at the locality scale in the Vhembe District, Limpopo Province, South Africa. The study area comprised 474 localities in Vhembe District for which smoothed malaria incidence curve were fitted with functional data method based on their weekly observed malaria incidence from July 2015 to June 2018. Then, hierarchical clustering algorithm was carried out considering different distances to classify the 474 smoothed malaria incidence curves. Thereafter, validity indices were used to determine the number of malaria incidence patterns. The cumulative malaria incidence of the study area was 4.1 cases/1000 person-years. Four distinct patterns of malaria incidence were identified: high, intermediate, low and very low with varying characteristics. Malaria incidence increased across transmission seasons and patterns. The localities in the two highest incidence patterns were mainly located around farms, and along the rivers. Some unusual malaria phenomena in Vhembe District were also highlighted as resurgence. Four distinct malaria incidence patterns were found in Vhembe District with varying characteristics. Findings show also unusual malaria phenomena in Vhembe District that hinder malaria elimination in South Africa. Assessing the factors associated with these unusual malaria phenome would be helpful on building innovative strategies that lead South Africa on malaria elimination.

Social deprivation and SARS-CoV-2 testing: a population-based analysis in a highly contrasted southern France region.

Background: Testing was the cornerstone of the COVID-19 epidemic response in most countries until vaccination became available for the general population. Social inequalities generally affect access to healthcare and health behaviors, and COVID-19 was rapidly shown to impact deprived population more drastically. In support of the regional health agency in Provence-Alpes-Côte d'Azur (PACA) in South-Eastern France, we analyzed the relationship between testing rate and socio-demographic characteristics of the population, to identify gaps in testing coverage and improve targeting of response strategies. Methods: We conducted an ecological analysis of SARS-CoV-2/COVID-19 testing rate in the PACA region, based on data aggregated at the finest spatial resolution available in France (IRIS) and by periods defined by public health implemented measures and major epidemiological changes. Using general census data, population density, and specific deprivation indices, we used principal component analysis followed by hierarchical clustering to define profiles describing local socio-demographic characteristics. We analyzed the association between these profiles and testing rates in a generalized additive multilevel model, adjusting for access to healthcare, presence of a retirement home, and the age profile of the population. Results: We identified 6 socio-demographic profiles across the 2,306 analyzed IRIS spatial units: privileged, remote, intermediate, downtown, deprived, and very deprived (ordered by increasing social deprivation index). Profiles also ranged from rural (remote) to high density urban areas (downtown, very deprived). From July 2020 to December 2021, we analyzed SARS-CoV-2/COVID-19 testing rate over 10 periods. Testing rates fluctuated strongly but were highest in privileged and downtown areas, and lowest in very deprived ones. The lowest adjusted testing rate ratios (aTRR) between privileged (reference) and other profiles occurred after implementation of a mandatory healthpass for many leisure activities in July 2021. Periods of contextual testing near Christmas displayed the largest aTRR, especially during the last periods of 2021 after the end of free convenience testing for unvaccinated individuals. Conclusion: We characterized in-depth local heterogeneity and temporal trends in testing rates and identified areas and circumstances associated with low testing rates, which the regional health agency targeted specifically for the deployment of health mediation activities.

Household living conditions and individual behaviours associated with malaria risk: a community-based survey in the Limpopo River Valley, 2020, South Africa.

BACKGROUND: Over the past decade, implementation of multiple malaria control strategies in most countries has largely contributed to advance the global malaria elimination agenda. Nevertheless, in some regions, seasonal epidemics may adversely affect the health of local populations. In South Africa, Plasmodium falciparum malaria is still present, with the Vhembe District experiencing an incidence rate of 3.79 cases/1000 person-years in 2018, particularly in the Limpopo River Valley, bordering Zimbabwe. To elucidate the complexity of the mechanisms involved in local regular malaria outbreaks, a community-based survey was implemented in 2020 that focused on the relationship between housing conditions and malaria risky behaviours. METHODS: The community-based cross-sectional survey was conducted among the population of three study sites in the Vhembe District, which were selected based on malaria incidence rate, social and health characteristics of inhabitants. The household survey used a random sampling strategy, where data were collected through face-to-face questionnaires and field notes; to described the housing conditions (housing questionnaire), and focus on individual behaviours of household members. Statistical analyses were performed combining hierarchical classifications and logistic regressions. RESULTS: In this study, 398 households were described, covering a population of 1681 inhabitants of all ages, and 439 adults who participated in community-based survey. The analysis of situations at risk of malaria showed that the influence of contextual factors, particularly those defined by the type of habitat, was significant. Housing conditions and poor living environments were factors of malaria exposure and history, regardless of site of investigation, individual preventive behaviours and personal characteristics of inhabitants. Multivariate models showed that, considering all personal characteristics or behaviours of inhabitants, housing conditions such as overcrowding pressures were significantly associated with individual malaria risk. CONCLUSIONS: The results showed the overwhelming weight of social and contextual factors on risk situations. Considering the Fundamental Causes Theory, malaria control policies based on health behaviour prevention, should reinforce access to care or promoting health education actions. Overarching economic development interventions in targeted geographical areas and populations have to be implemented, so that malaria control and elimination strategies can be efficiently and effectively managed.

SARS-CoV-2 seroprevalence and living conditions in Bamako (Mali): a cross-sectional multistage household survey after the first epidemic wave, 2020.

OBJECTIVES: In low-income settings with limited access to diagnosis, COVID-19 information is scarce. In September 2020, after the first COVID-19 wave, Mali reported 3086 confirmed cases and 130 deaths. Most reports originated from Bamako, with 1532 cases and 81 deaths (2.42 million inhabitants). This observed prevalence of 0.06% appeared very low. Our objective was to estimate SARS-CoV-2 infection among inhabitants of Bamako, after the first epidemic wave. We assessed demographic, social and living conditions, health behaviours and knowledges associated with SARS-CoV-2 seropositivity. SETTINGS: We conducted a cross-sectional multistage household survey during September 2020, in three neighbourhoods of the commune VI (Bamako), where 30% of the cases were reported. PARTICIPANTS: We recruited 1526 inhabitants in 3 areas, that is, 306 households, and 1327 serological results (≥1 years), 220 household questionnaires and collected answers for 962 participants (≥12 years). PRIMARY AND SECONDARY OUTCOME MEASURES: We measured serological status, detecting SARS-CoV-2 spike protein antibodies in blood sampled. We documented housing conditions and individual health behaviours through questionnaires among participants. We estimated the number of SARS-CoV-2 infections and deaths in the population of Bamako using the age and sex distributions. RESULTS: The prevalence of SARS-CoV-2 seropositivity was 16.4% (95% CI 15.1% to 19.1%) after adjusting on the population structure. This suggested that ~400 000 cases and ~2000 deaths could have occurred of which only 0.4% of cases and 5% of deaths were officially reported. Questionnaires analyses suggested strong agreement with washing hands but lower acceptability of movement restrictions (lockdown/curfew), and mask wearing. CONCLUSIONS: The first wave of SARS-CoV-2 spread broadly in Bamako. Expected fatalities remained limited largely due to the population age structure and the low prevalence of comorbidities. Improving diagnostic capacities to encourage testing and preventive behaviours, and avoiding the spread of false information remain key pillars, regardless of the developed or developing setting. ETHICS: This study was registered in the registry of the ethics committee of the Faculty of Medicine and Odonto-Stomatology and the Faculty of Pharmacy, Bamako, Mali, under the number: 2020/162/CA/FMOS/FAPH.

Malaria temporal dynamic clustering for surveillance and intervention planning.

BACKGROUND: Targeting interventions where most needed and effective is crucial for public health. Malaria control and elimination strategies increasingly rely on stratification to guide surveillance, to allocate vector control campaigns, and to prioritize access to community-based early diagnosis and treatment (EDT). We developed an original approach of dynamic clustering to improve local discrimination between heterogeneous malaria transmission settings. METHODS: We analysed weekly malaria incidence records obtained from community-based EDT (malaria posts) in Karen/Kayin state, Myanmar. We smoothed longitudinal incidence series over multiple seasons using functional transformation. We regrouped village incidence series into clusters using a dynamic time warping clustering and compared them to the standard, 5-category annual incidence standard stratification. RESULTS: We included 1115 villages from 2016 to 2020. We identified eleven P. falciparum and P. vivax incidence clusters which differed by amplitude, trends and seasonality. Specifically the 124 villages classified as "high transmission area" in the standard P. falciparum stratification belonged to the 11 distinct groups when accounting to inter-annual trends and intra-annual variations. Likewise for P. vivax, 399 "high transmission" villages actually corresponded to the 11 distinct dynamics. CONCLUSION: Our temporal dynamic clustering methodology is easy to implement and extracts more information than standard malaria stratification. Our method exploits longitudinal surveillance data to distinguish local dynamics, such as increasing inter-annual trends or seasonal differences, providing key information for decision-making. It is relevant to malaria strategies in other settings and to other diseases, especially when many countries deploy health information systems and collect increasing amounts of health outcome data. FUNDING: The Bill & Melinda Gates Foundation, The Global Fund against AIDS, Tuberculosis and Malaria (the Regional Artemisinin Initiative) and the Wellcome Trust funded the METF program.

Transmission of SARS-CoV-2 during indoor clubbing events: A clustered randomized, controlled, multicentre trial protocol.

Introduction: The SARS-CoV-2 pandemic led to the implementation of several non-pharmaceutical interventions (NPIs), from closings of bars and restaurants to curfews and lockdowns. Vaccination campaigns started hoping it could efficiently alleviate NPI. The primary objective of the "Indoor Transmission of COVID-19" (ITOC) study is to determine among a fully vaccinated population the relative risk of SARS-CoV-2 transmission during one indoor clubbing event. Secondary objectives are to assess the transmission of other respiratory viruses, risk exposure, and attitudes toward COVID-19 vaccination, health pass, and psychological impact of indoor club closing. Methods and analysis: Four thousand four hundred healthy volunteers aged 18-49 years and fully vaccinated will be included in Paris region. The intervention is an 8-hour indoor clubbing event with no masks, no social distance, maximum room capacity, and ventilation. A reservation group of up to 10 people will recruit participants, who will be randomized 1:1 to either the experimental group (2,200 volunteers in two venues with capacities of 1,000 people each) or the control group (2,200 volunteers asked not to go to the club). All participants will provide a salivary sample on the day of the experiment and 7 days later. They also will answer several questionnaires. Virological analyses include polymerase chain reaction (PCR) of salivary samples and air of the venue, investigating SARS-CoV-2 and 18 respiratory viruses. Ethics and dissemination: Ethical clearance was first obtained in France from the institutional review board (Comité de Protection des Personnes Ile de France VII - CPP), and the trial received clearance from the French National Agency for Medicines and Health Products (Agence National de Sécurité du Médicament - ANSM). The trial is supported and approved by The Agence Nationale Recherche sur le SIDA, les hépatites et maladies émergences (ANRS-MIE). Positive, negative, and inconclusive results will be published in peer-reviewed scientific journals. Trial registration number: IDR-CB 2021-A01473-38. Clinicaltrial.gov, identifier: NCT05311865.

Spatio-Temporal Variability of Malaria Incidence in the Health District of Kati, Mali, 2015-2019.

INTRODUCTION: Despite the implementation of control strategies at the national scale, the malaria burden remains high in Mali, with more than 2.8 million cases reported in 2019. In this context, a new approach is needed, which accounts for the spatio-temporal variability of malaria transmission at the local scale. This study aimed to describe the spatio-temporal variability of malaria incidence and the associated meteorological and environmental factors in the health district of Kati, Mali. METHODS: Daily malaria cases were collected from the consultation records of the 35 health areas of Kati's health district, for the period 2015-2019. Data on rainfall, relative humidity, temperature, wind speed, the normalized difference vegetation index, air pressure, and land use-land cover were extracted from open-access remote sensing sources, while data on the Niger River's height and flow were obtained from the National Department of Hydraulics. To reduce the dimension and account for collinearity, strongly correlated meteorological and environmental variables were combined into synthetic indicators (SI), using a principal component analysis. A generalized additive model was built to determine the lag and the relationship between the main SIs and malaria incidence. The transmission periods were determined using a change-point analysis. High-risk clusters (hotspots) were detected using the SatScan method and were ranked according to risk level, using a classification and regression tree analysis. RESULTS: The peak of the malaria incidence generally occurred in October. Peak incidence decreased from 60 cases per 1000 person-weeks in 2015, to 27 cases per 1000 person-weeks in 2019. The relationship between the first SI (river flow and height, relative humidity, and rainfall) and malaria incidence was positive and almost linear. A non-linear relationship was found between the second SI (air pressure and temperature) and malaria incidence. Two transmission periods were determined per year: a low transmission period from January to July-corresponding to a persisting transmission during the dry season-and a high transmission period from July to December. The spatial distribution of malaria hotspots varied according to the transmission period. DISCUSSION: Our study confirmed the important variability of malaria incidence and found malaria transmission to be associated with several meteorological and environmental factors in the Kati district. The persistence of malaria during the dry season and the spatio-temporal variability of malaria hotspots reinforce the need for innovative and targeted strategies.

Sub-national tailoring of seasonal malaria chemoprevention in Mali based on malaria surveillance and rainfall data.

BACKGROUND: In malaria endemic countries, seasonal malaria chemoprevention (SMC) interventions are performed during the high malaria transmission in accordance with epidemiological surveillance data. In this study we propose a predictive approach for tailoring the timing and number of cycles of SMC in all health districts of Mali based on sub-national epidemiological surveillance and rainfall data. Our primary objective was to select the best of two approaches for predicting the onset of the high transmission season at the operational scale. Our secondary objective was to evaluate the number of malaria cases, hospitalisations and deaths in children under 5 years of age that would be prevented annually and the additional cost that would be incurred using the best approach. METHODS: For each of the 75 health districts of Mali over the study period (2014-2019), we determined (1) the onset of the rainy season period based on weekly rainfall data; (ii) the onset and duration of the high transmission season using change point analysis of weekly incidence data; and (iii) the lag between the onset of the rainy season and the onset of the high transmission. Two approaches for predicting the onset of the high transmission season in 2019 were evaluated. RESULTS: In the study period (2014-2019), the onset of the rainy season ranged from week (W) 17 (W17; April) to W34 (August). The onset of the high transmission season ranged from W25 (June) to W40 (September). The lag between these two events ranged from 5 to 12 weeks. The duration of the high transmission season ranged from 3 to 6 months. The best of the two approaches predicted the onset of the high transmission season in 2019 to be in June in two districts, in July in 46 districts, in August in 21 districts and in September in six districts. Using our proposed approach would prevent 43,819 cases, 1943 hospitalisations and 70 deaths in children under 5 years of age annually for a minimal additional cost. Our analysis shows that the number of cycles of SMC should be changed in 36 health districts. CONCLUSION: Adapting the timing of SMC interventions using our proposed approach could improve the prevention of malaria cases and decrease hospitalisations and deaths. Future studies should be conducted to validate this approach.

Stratification at the health district level for targeting malaria control interventions in Mali.

Malaria is the leading cause of morbidity and mortality in Mali. Between 2017 and 2020, the number of cases increased in the country, with 2,884,827 confirmed cases and 1454 reported deaths in 2020. We performed a malaria risk stratification at the health district level in Mali with a view to proposing targeted control interventions. Data on confirmed malaria cases were obtained from the District Health Information Software 2, data on malaria prevalence and mortality in children aged 6-59 months from the 2018 Demographic and Health Survey, entomological data from Malian research institutions working on malaria in the sentinel sites of the National Malaria Control Program (NMCP), and environmental data from the National Aeronautics and Space Administration. A stratification of malaria risk was performed. Targeted malaria control interventions were selected based on spatial heterogeneity of malaria incidence, malaria prevalence in children, vector resistance distribution, health facility usage, child mortality, and seasonality of transmission. These interventions were discussed with the NMCP and the different funding partners. In 2017-2019, median incidence across the 75 health districts was 129.34 cases per 1000 person-years (standard deviation = 86.48). Risk stratification identified 12 health districts in very low transmission areas, 19 in low transmission areas, 20 in moderate transmission areas, and 24 in high transmission areas. Low health facility usage and increased vector resistance were observed in high transmission areas. Eight intervention combinations were selected for implementation. Our work provides an updated risk stratification using advanced statistical methods to inform the targeting of malaria control interventions in Mali. This stratification can serve as a template for continuous malaria risk stratifications in Mali and other countries.

Residential Mobility of a Cohort of Homeless People in Times of Crisis: COVID-19 Pandemic in a European Metropolis.

Most vulnerable individuals are particularly affected by the COVID-19 pandemic. This study takes place in a large city in France. The aim of this study is to describe the mobility of the homeless population at the beginning of the health crisis and to analyze its impact in terms of COVID-19 prevalence. From June to August 2020 and September to December 2020, 1272 homeless people were invited to be tested for SARS-CoV-2 antibodies and virus and complete questionnaires. Our data show that homeless populations are sociologically different depending on where they live. We show that people that were living on the street were most likely to be relocated to emergency shelters than other inhabitants. Some neighborhoods are points of attraction for homeless people in the city while others emptied during the health crisis, which had consequences for virus circulation. People with a greater number of different dwellings reported became more infected. This first study of the mobility and epidemiology of homeless people in the time of the pandemic provides unique information about mobility mapping, sociological factors of this mobility, mobility at different scales, and epidemiological consequences. We suggest that homeless policies need to be radically transformed since the actual model exposes people to infection in emergency.

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

Malaria 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.

Cold and dry winter conditions are associated with greater SARS-CoV-2 transmission at regional level in western countries during the first epidemic wave.

Higher transmissibility of SARS-CoV-2 in cold and dry weather conditions has been hypothesized since the onset of the COVID-19 pandemic but the level of epidemiological evidence remains low. During the first wave of the pandemic, Spain, Italy, France, Portugal, Canada and USA presented an early spread, a heavy COVID-19 burden, and low initial public health response until lockdowns. In a context when testing was limited, we calculated the basic reproduction number (R0) in 63 regions from the growth in regional death counts. After adjusting for population density, early spread of the epidemic, and age structure, temperature and humidity were negatively associated with SARS-CoV-2 transmissibility. A reduction of mean absolute humidity by 1 g/m3 was associated with a 0.15-unit increase of R0. Below 10 °C, a temperature reduction of 1 °C was associated with a 0.16-unit increase of R0. Our results confirm a dependency of SARS-CoV-2 transmissibility to weather conditions in the absence of control measures during the first wave. The transition from summer to winter, corresponding to drop in temperature associated with an overall decrease in absolute humidity, likely contributed to the intensification of the second wave in north-west hemisphere countries. Non-pharmaceutical interventions must be adjusted to account for increased transmissibility in winter conditions.

Accuracy of malaria diagnostic tests performed on non-invasively collected samples: a systematic review and meta-analysis.

BACKGROUND: During the last decade, many studies have assessed the performance of malaria tests on non-invasively collected specimens, but no systematic review has hitherto estimated the overall performance of these tests. We report here the first meta-analysis estimating the diagnostic performance of malaria diagnostic tests performed on saliva, urine, faeces, skin odour ('sniff and tell') and hair, using either microscopy or PCR on blood sample as reference test. METHODS: We searched on PubMed, EMBASE, African Journals Online and Cochrane Infectious Diseases from inception until 19 January 2021 for relevant primary studies. A random effects model was used to estimate the overall performance of various diagnostic methods on different types of specimen. RESULTS: Eighteen studies providing 30 data sets were included in the meta-analysis. The overall sensitivity, specificity and diagnostic OR (DOR) of PCR were 84.5% (95% CI 79.3% to 88.6%), 97.3% (95% CI 95.3% to 98.5%) and 184.9 (95% CI 95.8 to 356.9) in saliva, respectively; 57.4% (95% CI 41.4% to 72.1%), 98.6% (95% CI 97.3% to 99.3%) and 47.2 (95% CI 22.1 to 101.1) in urine, respectively. The overall sensitivity, specificity and DOR of rapid diagnostic test for malaria in urine was 59.8% (95% CI 40.0% to 76.9%), 96.9% (95% CI 91.0% to 99.0%) and 30.8 (95% CI:23.5 to 40.4). CONCLUSION: In settings where PCR is available, saliva and urine samples should be considered for PCR-based malaria diagnosis only if blood samples cannot be collected. The performance of rapid diagnostic testing in the urine is limited, especially its sensitivity. Malaria testing on non-invasively collected specimen still needs substantial improvement.

Factors associated with the spatial heterogeneity of the first wave of COVID-19 in France: a nationwide geo-epidemiological study.

BACKGROUND: The objective of this study was to better understand the factors associated with the heterogeneity of in-hospital COVID-19 morbidity and mortality across France, one of the countries most affected by COVID-19 in the early months of the pandemic. METHODS: This geo-epidemiological analysis was based on data publicly available on government and administration websites for the 96 administrative departments of metropolitan France between March 19 and May 11, 2020, including Public Health France, the Regional Health Agencies, the French national statistics institute, and the Ministry of Health. Using hierarchical ascendant classification on principal component analysis of multidimensional variables, and multivariate analyses with generalised additive models, we assessed the associations between several factors (spatiotemporal spread of the epidemic between Feb 7 and March 17, 2020, the national lockdown, demographic population structure, baseline intensive care capacities, baseline population health and health-care services, new chloroquine and hydroxychloroquine dispensations, economic indicators, degree of urbanisation, and climate profile) and in-hospital COVID-19 incidence, mortality, and case fatality rates. Incidence rate was defined as the cumulative number of in-hospital COVID-19 cases per 100 000 inhabitants, mortality rate as the cumulative number of in-hospital COVID-19 deaths per 100 000, and case fatality rate as the cumulative number of in-hospital COVID-19 deaths per cumulative number of in-hospital COVID-19 cases. FINDINGS: From March 19 to May 11, 2020, hospitals in metropolitan France notified a total of 100 988 COVID-19 cases, including 16 597 people who were admitted to intensive care and 17 062 deaths. There was an overall cumulative in-hospital incidence rate of 155·6 cases per 100 000 inhabitants (range 19·4-489·5), in-hospital mortality rate of 26·3 deaths per 100 000 (1·1-119·2), and in-hospital case fatality rate of 16·9% (4·8-26·2). We found clear spatial heterogeneity of in-hospital COVID-19 incidence and mortality rates, following the spread of the epidemic. After multivariate adjustment, the delay between the first COVID-19-associated death and the onset of the national lockdown was positively associated with in-hospital incidence (adjusted standardised incidence ratio 1·02, 95% CI 1·01-1·04), mortality (adjusted standardised mortality ratio 1·04, 1·02-1·06), and case fatality rates (adjusted standardised fatality ratio 1·01, 1·01-1·02). Mortality and case fatality rates were higher in departments with older populations (adjusted standardised ratio for populations with a high proportion older than aged >85 years 2·17 [95% CI 1·20-3·90] for mortality and 1·43 [1·08-1·88] for case fatality rate). Mortality rate was also associated with incidence rate (1·0004, 1·0002-1·001), but mortality and case fatality rates did not appear to be associated with baseline intensive care capacities. We found no association between climate and in-hospital COVID-19 incidence, or between economic indicators and in-hospital COVID-19 incidence or mortality rates. INTERPRETATION: This ecological study highlights the impact of the epidemic spread, national lockdown, and reactive adaptation of intensive care capacities on the spatial distribution of COVID-19 morbidity and mortality. It provides information for future geo-epidemiological analyses and has implications for preparedness and response policies to current and future epidemic waves in France and elsewhere. FUNDING: None.

Spatio-Temporal Dynamics of Plasmodium falciparum and Plasmodium vivax in French Guiana: 2005-2019.

Aims: This study examines the dynamics of malaria as influenced by meteorological factors in French Guiana from 2005 to 2019. It explores spatial hotspots of malaria transmission and aims to determine the factors associated with variation of hotspots with time. Methods: Data for individual malaria cases came from the surveillance system of the Delocalized Centers for Prevention and Care (CDPS) (n = 17) from 2005-2019. Meteorological data was acquired from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) database. The Box-Jenkins autoregressive integrated moving average (ARIMA) model tested stationarity of the time series, and the impact of meteorological indices (issued from principal component analysis-PCA) on malaria incidence was determined with a general additive model. Hotspot characterization was performed using spatial scan statistics. Results: The current sample includes 7050 eligible Plasmodium vivax (n = 4111) and Plasmodium falciparum (n = 2939) cases from health centers across French Guiana. The first and second PCA-derived meteorological components (maximum/minimum temperature/minimum humidity and maximum humidity, respectively) were significantly negatively correlated with total malaria incidence with a lag of one week and 10 days, respectively. Overall malaria incidence decreased across the time series until 2017 when incidence began to trend upwards. Hotspot characterization revealed a few health centers that exhibited spatial stability across the entire time series: Saint Georges de l'Oyapock and Antecume Pata for P. falciparum, and Saint Georges de l'Oyapock, Antecume Pata, Régina and Camopi for P. vivax. Conclusions: This study highlighted changing malaria incidence in French Guiana and the influences of meteorological factors on transmission. Many health centers showed spatial stability in transmission, albeit not temporal. Knowledge of the areas of high transmission as well as how and why transmission has changed over time can inform strategies to reduce the transmission of malaria in French Guiana. Hotspots should be further investigated to understand other influences on local transmission, which will help to facilitate elimination.