Search

Background: WHO and its partners have adopted alternative control interventions since the failure to eradicate malaria worldwide in the 1960s and 1970s. The aim of these interventions has been to redesign the control interventions to make them more effective and more efficient. The purpose of this study is to assess the population impact of control interventions implemented at the community health area level. Methods: The analysis used data from the health information system on malaria cases and interventions (distribution of long-lasting insecticide-treated nets (LLINs), seasonal malaria chemoprevention (SMC), access to rapid diagnostic tests (RDT), intermittent preventive treatment for pregnant women (IPT)) collected in the Kati health district from 2017 to 2020. And the contextual parameters (temperature, normal difference vegetation index (NDVI) and rainfall) were obtained by remote sensing. A generalizedadditive model was used to assess the impact of malaria control interventions on malaria cases as a function of meteorological factors. Results: The incidence of malaria varies from year to year and from health area to health area, as do meteorological factors in the study area. The distribution of long-lasting insecticide-treated nets, chemoprevention of seasonal malaria in children and access to rapid diagnostic tests for malaria were found to have a significant impact on the incidence of malaria in the population. Seasonal malaria chemoprevention was effective in reducing the incidence of malaria, while distribution of long-lasting insecticide-treated nets and access to rapid diagnostic tests increased with the number of malaria cases, reflecting efforts to distribute and use bed nets and to diagnose malaria cases among the population in the study area. Conclusion: The study showed the impact of SMC on reducing malaria cases in the population and the significant efforts in LLIN distribution and malaria case diagnosis. To further reduce the burden of malaria, sustained efforts and new interventions are needed, including improving access to rapid diagnosis and treatment in communities.

IntroductionThe spread of the COVID-19 pandemic, and its severity, is spatially heterogenous. At the individual level, the socioeconomic status (SES) profile is known to be associated with COVID-19 incidence and severity. The aim of this geo epidemiological study was to investigate the link between SES profile and potential confounders, and COVID-19 incidence and hospitalization rates, at a fine geographical scale.MethodsWe analyzed COVID-19 incidence and severity during two epidemic waves between September 2020 and June 2021, in Provence Alpes Côtes d’Azur, a 5 million inhabitants’ French region. The region is divided into sub-municipal areas that we have classified according to their SES profile. We then conducted a spatial analysis of COVID-19 indicators depending on SES profile, age structure, and health services provision. This analysis considered spatial autocorrelation between areas.ResultsCOVID-19 incidence rates in more deprived areas were similar to those in wealthiest ones. Hospitalization rates of COVID-19 cases in conventional care units were greater in more deprived vs wealthiest areas: Standardized Incidence Ratio (SIR) were respectively 1.34 [95% confidence interval 1.18 - 1.52] and 1.25 [1.13 - 1.38] depending on the epidemic wave. This gap was even greater regarding hospitalization rates of cases in critical care units: SIR = 1.64 [1.30 - 2.07] then 1.33 [1.14 - 1.55] depending on the epidemic wave. Hospitalization rates of COVID-19 cases in conventional care units were also greater in areas with high proportion of elderly people vs young people: SIR respectively 1.24 [1.11 - 1.38] and 1.22 [1.13 - 1.32] depending on the wave.ConclusionConsidering age structure and health services provision, a deprived SES profile is associated to a greater COVID-19 severity in terms of hospitals admissions, in conventional care units and in critical care units. This result implies targeting risk prevention efforts on these areas in pandemic situations, and highlights the need to develop access to healthcare to deprived populations in anticipation of periods of crisis.Key messagesWhat is already known on this topic- Socioeconomic status is associated to COVID-19 incidence and severity, at an individual scale or at a large spatial scale.What this study adds- We showed the positive relationship between deprivation and COVID-19 incidence and hospitalization rates at a fine sub-municipal geographical scale. We considered confusion factors like demographic structure and health services provision.How this study might affect research, practice or policy- These findings may help predict at a fine scale where the impact will be most severe in pandemic situations and make it possible to target risk prevention efforts on these areas.

Antibiotic resistance of bacterial pathogens is considered by the World Health Organization as a major threat to global health aggravated by the misuse of antibiotics. In clinical practice results of bacterial cultures and antibiograms can take several days. In the meantime, prescribing an empirical antimicrobial treatment constitutes a challenge in which the practitioner has to strike a balance between antibiotics spectrum and expected susceptibility probability. In this contribution, we report the development and testing of a machine-learning-based system that early predicts the antimicrobial susceptibility probability and provides explanations of the contribution of the different cofactors at 4 different stages prior to the antibiogram (sampling, direct examination, culture, and species identification stages). A comparative analysis of different state of the art machine learning and probabilistic methods was carried out using 7 years of historical bacterial resistance data from the Hôpital Européen Marseille, France. Our results suggest that dense neural network-based models and Bayesian models are suitable to early predict antibiotics susceptibility (average AUC 0.91 at the species identification stage) even for the less frequent situations.

Background The South African population at risk of malaria represents 10% (i.e., six million inhabitants) of the population in three provinces: Limpopo, Mpumalanga and KwaZulu-Natal. In Limpopo Province, Vhembe District is most affected, showing an incidence of 3.8 cases/1000 person-years in 2018. Stratification of malaria intensity level is part of the World Health Organization (WHO) recommendations to accelerate malaria elimination. There are no studies on malaria incidence at locality level, due to difficulty of population availability at this scale. This study aimed to identify and describe malaria incidence patterns at locality level in Vhembe District. Method Using the functional data method, a smooth function (functional data or curve) was fitted from the time series of observed malaria incidence for each of the 474 localities in Vhembe District from July 2015 to June 2018, representing three malaria seasons. These 474 smooth functions were classified using hierarchical clustering (Ward's method) with testing several dissimilarity measures. Thereafter, validity indices measured from these classifications were used to determine the number of distinct temporal patterns of malaria incidence. Results The observed malaria incidence in the 474 localities in Vhembe District was 4.1 cases/1000 person-years. Four distinct patterns of malaria incidence were identified: high, intermediate, low and very low, including 9, 20, 54 and 391 localities and a cumulative observed malaria incidence of 181.2, 54.1, 16.2 and 2.4 cases/1000 person-years, respectively. Malaria incidence increased sharply in high and intermediate incidence patterns over high transmission periods, and over the last low transmission period 2017/2018. These two high incidence patterns were in the Limpopo River Valley, mostly around farms, and in localities along the Mutale River. Conclusion This study showed four malaria incidence patterns in Vhembe District with varying characteristics. Findings show unusual malaria phenomena in Vhembe District, including a high incidence level during a low transmission season and occurrence of a series of resurgences. South Africa has reached the malaria pre-elimination stage, based on development of access to diagnostics, treatment and vector control. However, the recent malaria resurgence in remote areas hinders malaria elimination, highlighting the need for assessing resurgence determinants and developing innovative targeted malaria elimination strategies.

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.

ContextIn low-income settings where access to biological diagnosis is limited, data on the spread of the COVID-19 epidemic are scarce. In September 2020, after the first COVID-19 wave, Mali reported 3,086 confirmed cases and 130 deaths. Most reports originated form Bamako, the capital city, with 1,532 reported cases and 81 deaths for an estimated 2.42 million population. 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 also assessed demographic, social and living conditions, health behaviors and knowledge associated with SARS-CoV-2 seropositivity.Material and methodsWe conducted a cross-sectional multistage cluster household survey in commune VI, which reported, September 2020, 30% (n=466) of the total cases reported at Bamako. We measured serological status by detection of SARS-CoV-2 spike protein Antibodies in venous blood sampled after informed consent. We documented housing conditions and individual health behaviors through KABP questionnaires among participants aged 12 years and older. We estimated the number of SARS-CoV-2 infections and deaths in the total population of Bamako using the age and sex distributions of SARS-CoV-2 seroprevalence. A logistic generalized additive multilevel model was performed to estimate household conditions and demographic factors associated with seropositivity.ResultsWe recruited 1,526 inhabitants in the 3 investigated areas (commune VI, Bamako) belonging to the 306 sampled households. We obtained 1,327 serological results, 220 household questionnaires and collected KABP answers for 962 participants. The prevalence of SARS-CoV-2 seropositivity was 16.4% after adjusting on the population structure. This suggested that ∼400,000 cases and ∼ 2,000 deaths could have occurred of which only 0.4% of cases and 5% of deaths were officially reported. KABP analyses suggested strong agreement with washing hands but lower acceptability of movement restrictions (lockdown or curfew), and limited mask wearing.ConclusionIn spite of limited numbers of reported cases, 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. This highlight the difficulty of developing epidemic control strategies when screening test are not available or not used, even more when the transmission modalities are not well known by the population. Targeted policies based on health education prevention have to be implemented to improve the COVID-19 risk perception among the local population and fight to false knowledge and beliefs.

International audience; The occurrence of malaria resurgences could threaten progress toward elimination of the disease. This study investigated the impact of repeated renewal of long-lasting insecticide-treated net (LLIN) universal coverage on malaria resurgence over a period of 10 years of net implementation in Dielmo (Senegal). A longitudinal study was carried out in Dielmo between August 2007 and July 2018. In July 2008, LLINs were offered to all villagers through universal campaign distribution which was renewed in July 2011, August 2014, and May 2016. Malaria cases were treated with artemisinin-based combination therapy. Two resurgences of malaria occurred during the 10 years in which LLINs have been in use. Since the third renewal of the nets, malaria decreased significantly compared with the first year the nets were implemented (adjusted incidence rate ratio) (95% CI) = 0.35 (0.15-0.85), during the ninth year after net implementation). During the tenth year of net implementation, no cases of malaria were observed among the study population. The use of nets increased significantly after the third time the nets were renewed when compared with the year after the first and the second times the nets were renewed (P < 0.001). The third renewal of nets, which took place after 2 years instead of 3 years together with a higher use of LLINs especially among the young, probably prevented the occurrence of a third malaria upsurge in this village.

International audience; Centre Department, Haiti, was the origin of a major cholera epidemic during 2010-2019. Although no fine-scale spatial delineation is officially available, we aimed to analyze determinants of cholera at the local level and identify priority localities in need of interventions. After estimating the likely boundaries of 1,730 localities by using Voronoi polygons, we mapped 5,322 suspected cholera cases reported during January 2015-September 2016 by locality alongside environmental and socioeconomic variables. A hierarchical clustering on principal components highlighted 2 classes with high cholera risk: localities close to rivers and unimproved water sources (standardized incidence ratio 1.71, 95% CI 1.02-2.87; p = 0.04) and urban localities with markets (standardized incidence ratio 1.69, 95% CI 1.25-2.29; p = 0.0006). Our analyses helped identify and characterize areas where efforts should be focused to reduce vulnerability to cholera and other waterborne diseases; these methods could be used in other contexts.

Objective:Despite the existence of various levels of infection prevention and control (IPC) measures aimed at limiting the transmission of vancomycin-resistant enterococci (VRE) in hospitals, these measures are sometimes difficult to implement. Using an agent-based model (ABM), we simulated the transmission of VRE within and between 3 care units according to different IPC measures.Methods:The ABM was modelled on short-stay medical wards, represented by 2 conventional care units and 1 intensive care unit. The scenarios consisted of the simulation of various compliance rates of caregivers with regard to hand hygiene (HH) in different contexts of IPC measures: (1) standard precautions for all patients, (2) additional contact precautions for VRE-carrier patients, (3) geographical cohorting of carrier patients, and (4) creation of an isolation unit with dedicated staff.Results:With Conclusions:The present ABM showed that while contact precautions, geographic cohorting, and an isolation unit may represent good complements to standard precautions, they may theoretically not be necessary if HH is followed at a high level of compliance.

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.

Background In malaria endemic countries, control interventions are performed during the high malaria transmission season using epidemiological surveillance data. One such intervention, seasonal chemoprevention (SMC), consists of the monthly administration of antimalarial drugs to children under 5 years. This study proposes an anticipating approach for adapting the timing of SMC interventions in Mali and the number of rounds. Our primary objective was to select the best approach for anticipating the onset of the high transmission season in the different health districts of Mali based on epidemiological surveillance and rainfall data. Our secondary objective was to evaluate the number of malaria cases, hospitalisations, and deaths in children under 5 years that could be prevented in Mali using the selected approach and the additional cost associated.Method Confirmed malaria cases and weekly rainfall data were collected for the 75 health districts of Mali for the 2014-2019 period. The onset of the rainy season, the onset of the high transmission season, the lag between these two events and the duration of the high transmission season were determined for each health district. Two approaches for anticipating the onset of the high transmission season in 2019 were evaluated. Results In 2014-2019, the onset of the rainy season ranged from W17 April to W34 August and that of the high transmission season 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 approach anticipated the onset of the high transmission season 2019 in June in 2 districts, July in 46 districts, August in 21 districts and September in 6 districts. Using this approach over the 2014-2019 period would have led to changing the timing of SMC interventions in 36 health districts and would have prevented 43,819 cases, 1,943 hospitalisations and 70 deaths in children under 5 years. The additional cost of using our proposed approach is less than 5% of the current approach. Conclusion Adapting the timing of SMC interventions using our proposed approach would improve the prevention of malaria cases, hospitalisations, and deaths for a reasonable additional cost.

BackgroundAfter a global decline, malaria cases re-increases have been shown recently.The aim of this analysis was to update the epidemiological facies of malaria in Burkina Faso (around 4% of malaria cases worldwide) by estimating weekly malaria incidences at health district levels, from 2013 to 2018, associated to environmental and meteorological factors.MethodsMalaria cases and deaths weekly reports were extracted from the National Malaria Control Program for each health district from 2013 to 2018. Population data were extracted from the reports of the national statistics council. Environmental data were collected through remote sensing.After estimating incidence through time and space, trend was assessed by an additive decomposition of the incidence and malaria seasons of transmission was estimated by change point analysis (PELT algorithm).Incidence maps for each year of the study period were assessed to highlight spatial variability through years. Maps of rainfall, temperature, and vegetation (NDVI) were produced to characterize the health district environmental variability.ResultsIn 2013, 775 cases /100,000 inhab.week were observed in average, and remain roughly constant until 2015. Malaria re-increased from 2016, reaching 2428 cases /100,000 inhab.week in 2018.From 2013 to 2016, two transmission periods were observed: low from January to July (included) and high from August to December (included).From 2017 to 2018, an intermediate transmission period from mid-November to early January intercalated between the low transmission period from mid-February to early June and the high transmission period from July to late DecemberFrom 2013 to 2015, the most affected districts were located in the center and central-eastern part of the country. From 2016 to 2018 all health districts, except those in the Sahel region, were affected with at least 45,000 cases per 100,000 persons/year. This south-to-north gradient was also observed with rainfall, temperature and NDVI.ConclusionMalaria incidences re-increased through years and across the country since 2016. But no modification of the environmental factor variability was observed during the same period, in time or space. The re-increase of malaria in Burkina Faso could be due to a real increase of the disease, or to a better access to diagnostic and cure, together with the development of the epidemiological information system.

IntroductionMalaria has been the leading cause of morbidity and mortality for several decades in Mali, with an increase from 2017 to 2020 (2,884,837 confirmed cases and 1,454 deaths). On the recommendation of the World Health Organization (WHO) and in the interests of efficient use of resources, Mali has begun a process of stratifying the health districts to target malaria control strategies.MethodMalaria, entomological and environmental data were collected through the local health information system (LHIS), the Demographic and Health Survey (DHS 2018), research institutions and MALI-METEO services. The WHO has recommended stratification at the district level consisted of assigning each district to one of 4 classes according to criteria based on incidence adjusted for attendance rate. Variables associated with monthly malaria incidence at the district level were identified using a general additive non-linear regression model.ResultsFrom 2017 to 2019, the median incidence across 75 health districts of Mali was 129.34 cases per 1,000 person-year (IQR=86.48). The results showed different periods of high malaria transmission in health districts level and durations varying from 2 to 6 months, showing a double peak for some health districts, which were located in the flooded areas. environmental variables such as rainfall, vegetation index (NDVI), maximum temperature and relative humidity were significantly associated at malaria incidence with a lag of around one month. A strata defines a geographical area with similar epidemiological, environmental and socio-economic factors. Stratification resulted in 12 health districts of very low transmission, 19 low transmission, 20 moderate transmission and 24 in high transmission areas. The number of rounds of season malaria chemoprevention will be based on the number of months in the high transmission period.ConclusionThis first stratification in Mali will allow targeting malaria control strategies. This approach will be dynamic and revised yearly in order to integrate information from the national epidemiological surveillance.

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., info:eu-repo/semantics/published

International audience; BACKGROUND:The widespread use of artemisinin-based combination therapy (ACT) and long-lasting insecticide-treated nets (LLINs) has led to an impressive decrease of malaria burden these recent years in Africa. However, some new challenges about the future of malaria control and elimination efforts have appeared. Among these challenges, the loss and-or-the only partial acquisition of anti-Plasmodium immunity among exposed populations lead to an increase of the age at risk of malaria. Indeed, older children and adults may become more vulnerable to malaria. Studies about malaria among adults seemed, therefore, important. This study investigated the evolution of malaria morbidity in adults of Dielmo (Senegal) before and after the implementation of LLINs.METHODS:From August 2007 to July 2015, a longitudinal study involving adults above 15 years old was carried out in Dielmo, where ACT was introduced in June 2006 and LLINs in July 2008. In July 2011 and August 2014, all LLINs were renewed. The presence of each person in the village was monitored daily. Thick smears associated lately with rapid diagnosis test (RDT) and quantitative polymerase chain reaction methods were performed for all cases of fever. To assess malaria prevalence, thick smears and RDT were performed quarterly in all individuals. Malaria risks factors were assessed using negative binomial regression mixed-model based on person-trimester observations.RESULTS:Malaria morbidity among adults has decreased significantly since the implementation of LLINs in Dielmo. However, malaria resurgences have occurred twice during the 7 years of LLINs use. During these malaria resurgences, the overall incidence of malaria among adults was similar to the incidence during the year before the implementation of LLINs (adjusted incidence rate ratio [95% CI] aIRR = 1.04 [0.66-1.64], p = 0.88 and aIRR = 1.16 [0.74-1.80], p = 0.52 during the first and the second malaria resurgence period, respectively). Younger adults were most vulnerable during these malaria upsurges as the incidence of malaria increased significantly among them (χ2 = 5.2; p = 0.02).CONCLUSION:Malaria among adults especially younger adults should deserve more attention in the areas where malaria was previously endemic as they became vulnerable probably because of the partial acquisition and-or-the loss of anti-Plasmodium relative immunity and the non regular use of LLINs.

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 to SARS-CoV-2 transmissibility. A reduction of mean absolute humidity by 1g/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-like conditions likely contributed to the intensification of the second wave in north-west hemisphere countries. Adjustments of the levels of social mobility restrictions need to account for increased SARS-CoV-2 transmissibility in winter conditions.

International audience; Annual influenza vaccination is recommended for children with chronic diseases. Studies on influenza vaccines, following controversies related to the 2009 H1N1 influenza, are scarce in Europe. Our aim was to evaluate the influenza vaccination coverage in such children in a French tertiary hospital. Secondary objectives were the evaluation of the influenza vaccination coverage trend and the identification of factors influencing the vaccination status. A prospective and descriptive study by questionnaire was performed at the end of 2017 in 402 French hospital outpatients with various underlying chronic diseases eligible to the influenza vaccination. The 2016-2017 vaccination coverage was 46.5%. Figures of 75% or greater were only found in patients with cystic fibrosis and sickle cell disease. CART analysis identified vaccination in the previous year, medical recommendation for vaccination, and maternal influenza vaccination as a child's decisive factors for being vaccinated.Conclusion: Influenza vaccination coverage remains insufficient in children receiving hospital follow-up for chronic diseases. Its implementation clearly depends on pediatricians' recommendation to vaccinate and on the type of chronic disease. What is Known: • Despite health policy recommendations, the rate of annual influenza vaccination in children with chronic diseases is low What is New: • Influenza vaccination coverage depends on the type of chronic disease and on the pediatricians' counseling to vaccine.

International audience

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&ndash, 2019. Meteorological data was acquired from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) database. The Box&ndash, Jenkins autoregressive integrated moving average (ARIMA) model tested stationarity of the time series, and the impact of meteorological indices (issued from principal component analysis&mdash, 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&rsquo, Oyapock and Antecume Pata for P. falciparum, and Saint Georges de l&rsquo, Oyapock, Antecume Pata, R&eacute, gina 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.

Introduction Mettre en œuvre des strategies de lutte contre les maladies transmissibles necessite la comprehension des dynamiques epidemiques a une echelle geographique precise et des facteurs environnementaux associes. Dans cette etude de geo-epidemiologie, l’objectif etait de determiner les facteurs environnementaux associes a la dynamique du paludisme ainsi que les « hotspots », en fonction des periodes de risques differents, pour optimiser l’acces aux soins et aux mesures de prevention. Methodes L’etude s’est deroulee dans 27 villages (7408 habitants) du district sanitaire de Diebougou au sud-ouest du Burkina Faso (13 centres de sante). Une detection passive des cas en centres de sante a ete realisee de janvier 2016 a debut septembre 2017. Les donnees meteorologiques ont ete collectees par teledetection (ERA-5). Les clusters a haut risque ont ete detectes avec la methode de balayage de Kulldorf. L’incidence des cas de paludisme a ete modelise a l’aide d’un modele additif generalise mixte multi-niveaux (GAMM) (villages imbriques dans les centres de sante). Un champ gaussien et une structure AR 1 ont ete mis en œuvre pour prendre en compte les autocorrelations spatiale et temporelle. Les relations non-lineaires avec les facteurs meteorologiques ont ete modelisees a l’aide de fonctions splines. Des ratios standardises d’incidence (RSI) ont ete estimes par parties, sur la base des predicteurs non-lineaires. Enfin, ce modele a ete teste par prediction des cas sur 2016 et 2017. Resultats Au total, 3179 cas de paludisme ont ete enregistres correspondant a une incidence de 429,13 cas pour 1000 personnes-annee avec en moyenne 61,13 cas par semaine. Nous avons detecte 4 clusters a haut risque qui cumulent 1685 cas pour 1973 habitants soit un taux d’incidence moyen de 854,02 cas pour 1000 habitants-annee. Ces clusters etaient localises au sud et au centre de la zone d’etude. La modelisation GAMM a mis en evidence une variabilite des cas plus forte entre centres de sante (ecart-type Sd = 5,74) qu’entre les villages dependant d’un meme centre de sante (ecart-type Sd = 0,69). La relation entre le nombre de cas et les predicteurs associes aux precipitations etait positive et presque lineaire avec un RSI variant de 1,07 (IC95 % = [1,03–1,10]) a 1,14 (IC95 % = [1,14–1,16]). Pour les predicteurs associes aux temperatures, une relation positive non lineaire a ete estimee, avec une augmentation des cas uniquement pour les valeurs positives et un RSI d’abord constant puis augmentant, variant de 0,99 (IC95 % = [0,93–1,05]) a 1,37 (IC95 % = [1,36–1,37]). La distance des villages aux centres de sante n’etait pas associee aux cas de paludisme (p = 0,78). Le modele predisait ainsi avec un retard de trois semaines le demarrage du pic epidemique de l’annee suivante. Conclusion Dans cette etude nous avons pu montrer l’heterogeneite spatiale des cas et mis en evidence des hotspots de paludisme, meme a une echelle precise (village). Outre la mise en evidence de zone geographique plus touchees que d’autres, notre approche peut etre utilisee en routine pour identifier les zones ou les strategies de lutte doivent etre priorisees.

In central Senegal, malaria incidence declined in response to scaling-up of control measures from 2000 to 2010 and has since remained stable, making elimination unlikely in the short term. Additional control measures are needed to reduce transmission. We simulated chemoprophylaxis interventions targeting malaria hotspots using a metapopulation mathematical model, based on a differential-equation framework and incorporating human mobility. The model was fitted to weekly malaria incidence from 45 villages. Three approaches for selecting intervention targets were compared: (a) villages with malaria cases during the low transmission season of the previous year, (b) villages with highest incidence during the high transmission season of the previous year, (c) villages with highest connectivity with adjacent populations. Our results showed that intervention strategies targeting hotspots would be effective in reducing malaria incidence in both targeted and untargeted areas. Regardless of the intervention strategy used, pre-elimination (1&ndash, 5 cases per 1000 per year) would not be reached without simultaneously increasing vector control by more than 10%. A cornerstone of malaria control and elimination is the effective targeting of strategic locations. Mathematical tools help to identify those locations and estimate the impact in silico.

Like in many countries and regions, spread of the COVID-19 pandemic has exhibited important spatial heterogeneity across France, one of the most affected countries so far.To better understand factors associated with incidence, mortality and lethality heterogeneity across the 96 administrative departments of metropolitan France, we thus conducted a geo-epidemiological analysis based on publicly available data, using hierarchical ascendant classification (HAC) on principal component analysis (PCA) of multidimensional variables, and multivariate analyses with generalized additive models (GAM).Our results confirm a marked spatial heterogeneity of in-hospital COVID-19 incidence and mortality, following the North East – South West diffusion of the epidemic. The delay elapsed between the first COVID-19 associated death and the onset of the national lockdown on March 17th, 2020, appeared positively associated with in-hospital incidence, mortality and lethality. Mortality was also strongly associated with incidence. Mortality and lethality rates were significantly higher in departments with older population, but they were not significantly associated with the number of intensive-care beds available in 2018. We did not find any significant association between incidence, mortality or lethality rates and incidence of new chloroquine and hydroxychloroquine dispensations in pharmacies either, nor between COVID-19 incidence and climate, nor between economic indicators and in-hospital COVID-19 incidence or mortality.This ecological study highlights the impact of population age structure, epidemic spread and transmission mitigation policies in COVID-19 morbidity or mortality heterogeneity.

Background: Previous controlled studies demonstrated seasonal malaria chemoprevention (SMC) reduces malaria morbidity by &gt, 80% in children aged 3&ndash, 59 months. Here, we assessed malaria morbidity after large-scale SMC implementation during a pilot campaign in the health district of Koutiala, Mali. Methods: Starting in August 2012, children received three rounds of SMC with sulfadoxine-pyrimethamine (SP) and amodiaquine (AQ). From July 2013 onward, children received four rounds of SMC. Prevalence of malaria infection, clinical malaria and anemia were assessed during two cross-sectional surveys conducted in August 2012 and June 2014. Investigations involved 20 randomly selected clusters in 2012 against 10 clusters in 2014. Results: Overall, 662 children were included in 2012, and 670 in 2014. Children in 2014 versus those surveyed in 2012 showed reduced proportions of malaria infection (12.4% in 2014 versus 28.7% in 2012 (p = 0.001)), clinical malaria (0.3% versus 4.2%, respectively (p &lt, 0.001)), and anemia (50.1% versus 67.4%, respectively (p = 0.001)). A propensity score approach that accounts for environmental differences showed that SMC conveyed a significant protective effect against malaria infection (IR = 0.01, 95% CI (0.0001, 0.09), clinical malaria (OR = 0.25, 95% CI (0.06, 0.85)), and hemoglobin concentration (&beta, = 1.3, 95% CI (0.69, 1.96)) in 2012 and 2014, respectively. Conclusion: SMC significantly reduced frequency of malaria infection, clinical malaria and anemia two years after SMC scale-up in Koutiala.

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012&ndash, 2017) from 1400 persons who sought treatment at Dangassa&rsquo, s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels &gt, 65%, combined with two or more consecutive rain episodes and a mean wind speed &lt, 1.8 m/s, (2) among the three models, the FGLM obtained the best results in terms of prediction, and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

Background: According to the World Health Organization, there were more than 228 million cases of malaria globally in 2018, with 93% of cases occurring in Africa, in Mali, a 13% increase in the number of cases was observed between 2015 and 2018, this study aimed to evaluate the impact of meteorological and environmental factors on the geo-epidemiology of malaria in the health district of Dire, Mali. Methods: Meteorological and environmental variables were synthesized using principal component analysis and multiple correspondence analysis, the relationship between malaria incidence and synthetic indicators was determined using a multivariate general additive model, hotspots were detected by SaTScan. Results: Malaria incidence showed high inter and intra-annual variability, the period of high transmission lasted from September to February, health areas characterized by proximity to the river, propensity for flooding and high agricultural yield were the most at risk, with an incidence rate ratio of 2.21 with confidence intervals (95% CI: 1.85&ndash, 2.58), malaria incidence in Dire declined from 120 to 20 cases per 10,000 person-weeks between 2013 and 2017. Conclusion: The identification of areas and periods of high transmission can help improve malaria control strategies.

Malaria transmission largely depends on environmental, climatic, and hydrological conditions. In Mali, malaria epidemiological patterns are nested within three ecological zones. This study aimed at assessing the relationship between those conditions and the incidence of malaria in Dangassa and Koila, Mali. Malaria data was collected through passive case detection at community health facilities of each study site from June 2015 to January 2017. Climate and environmental data were obtained over the same time period from the Goddard Earth Sciences (Giovanni) platform and hydrological data from Mali hydraulic services. A generalized additive model was used to determine the lagged time between each principal component analysis derived component and the incidence of malaria cases, and also used to analyze the relationship between malaria and the lagged components in a multivariate approach. Malaria transmission patterns were bimodal at both sites, but peak and lull periods were longer lasting for Koila study site. Temperatures were associated with malaria incidence in both sites. In Dangassa, the wind speed (p = 0.005) and river heights (p = 0.010) contributed to increasing malaria incidence, in contrast to Koila, where it was humidity (p &lt, 0.001) and vegetation (p = 0.004). The relationships between environmental factors and malaria incidence differed between the two settings, implying different malaria dynamics and adjustments in the conception and plan of interventions.

One of the major contributors of malaria-related deaths in Sub-Saharan African countries is the limited accessibility to quality care. In these countries, malaria control activities are implemented at the health-district level (operational entity of the national health system), while malaria readiness indicators are regionally representative. This study provides an approach for estimating health district-level malaria readiness indicators from survey data designed to provide regionally representative estimates. A binomial-hierarchical Bayesian spatial prediction method was applied to Burkina Faso Service Availability and Readiness Assessment (SARA) survey data to provide estimates of essential equipment availability and readiness for malaria care. Predicted values of each indicator were adjusted by the type of health facility, location, and population density. Then, a health district composite readiness profile was built via hierarchical ascendant classification. All surveyed health-facilities were mandated by the Ministry of Health to manage malaria cases. The spatial distribution of essential equipment and malaria readiness was heterogeneous. Around 62.9% of health districts had a high level of readiness to provide malaria care and prevention during pregnancy. Low-performance scores for managing malaria cases were found in big cities. Health districts with low coverage for both first-line antimalarial drugs and rapid diagnostic tests were Baskuy, Bogodogo, Boulmiougou, Nongr-Massoum, Sig-Nonghin, Dafra, and Do. We provide health district estimates and reveal gaps in basic equipment and malaria management resources in some districts that need to be filled. By providing local-scale estimates, this approach could be replicated for other types of indicators to inform decision makers and health program managers and to identify priority areas., info:eu-repo/semantics/published

Background Effective targeting of malaria control in low transmission areas requires identification of transmission foci or hotspots. We investigated the use of functional data analysis to identify and describe spatio-temporal pattern of malaria incidence in an area with seasonal transmission in west-central Senegal. Method Malaria surveillance was maintained over 5 years from 2008 to 2012 at health facilities serving a population of 500,000 in 575 villages in two health districts in Senegal. Smooth functions were fitted from the time series of malaria incidence for each village, using cubic B-spline basis functions. The resulting smooth functions for each village were classified using hierarchical clustering (Ward’s method), using several different dissimilarity measures. The optimal number of clusters was then determined based on four cluster validity indices, to determine the main types of distinct temporal pattern of malaria incidence. Epidemiological indicators characterizing the resulting malaria incidence pattern in terms of the timing of seasonal outbreaks, were calculated based on the slope (velocity) and rate of change of the slope (acceleration) of the incidence over time. Results Three distinct patterns of malaria incidence were identified. A pattern characterized by high incidence, in 12/575 (2%) villages, with average incidence of 114 cases/1000 person-years over the 5 year study period; a pattern with intermediate incidence in 97 villages (17%), with average incidence of 13 cases/1000 person-years; and a pattern with low incidence in 466 (81%) villages, with average incidence 2.6 cases/1000 person-years. Epidemiological indicators characterizing the fluctuations in malaria incidence showed that seasonal outbreaks started later, and ended earlier, in the low incidence pattern. Conclusion Functional data analysis can be used to classify communities based on time series of malaria incidence, and to identify high incidence communities. Indicators can be derived from the fitted functions which characterize the timing of outbreaks. These tools may help to better target control measures.

International audience; Importance: Because inadvertent damage of parathyroid glands can lead to postoperative hypocalcemia, their identification and preservation, which can be challenging, are pivotal during total thyroidectomy.Objective: To determine if intraoperative imaging systems using near-infrared autofluorescence (NIRAF) light to identify parathyroid glands could improve parathyroid preservation and reduce postoperative hypocalcemia.Design, setting, and participants: This randomized clinical trial was conducted from September 2016 to October 2018, with a 6-month follow-up at 3 referral hospitals in France. Adult patients who met eligibility criteria and underwent total thyroidectomy were randomized. The exclusion criteria were preexisting parathyroid diseases.Interventions: Use of intraoperative NIRAF imaging system during total thyroidectomy.Main outcomes and measures: The primary outcome was the rate of postoperative hypocalcemia (a corrected calcium

International audience; To date, there is no effective treatment to cure dengue fever, a mosquito-borne disease which has a major impact on human populations in tropical and subtropical regions. Although the characteristics of dengue infection are well known, factors associated with landscape are highly scale dependent in time and space, and therefore difficult to monitor. We propose here a mapping review based on 78 articles that study the relationships between landscape factors and urban dengue cases considering household, neighborhood and administrative levels. Landscape factors were retrieved from survey questionnaires, Geographic Information Systems (GIS), and remote sensing (RS) techniques. We structured these into groups composed of land cover, land use, and housing type and characteristics, as well as subgroups referring to construction material, urban typology, and infrastructure level. We mapped the co-occurrence networks associated with these Remote Sens. 2020, 12, 932 2 of 82 factors, and analyzed their relevance according to a three-valued interpretation (positive, negative, non significant). From a methodological perspective, coupling RS and GIS techniques with field surveys including entomological observations should be systematically considered, as none digital land use or land cover variables appears to be an univocal determinant of dengue occurrences. Remote sensing urban mapping is however of interest to provide a geographical frame to distribute human population and movement in relation to their activities in the city, and as spatialized input variables for epidemiological and entomological models.

Objectives Because of methodological biases and statistical issues, individual age estimation has been considered too imprecise in reconstructing valid palaeodemographic mortality profiles. Recently, the standardized procedure of cementochronology (the tooth cementum annulations method) has reduced technical biases, thus increasing the accuracy of age estimates. This study aims to test the reliability of cementochronology in estimating the age distribution of an archaeological sample to then build the corresponding abridged life table to assess demographic parameters of the living population. Materials and methods By combining cementochronology with probability density analysis, we assessed the cumulative probabilistic age-at-death distribution of 109 adults buried between the 16th and 18th centuries in Notre-Dame-du-Bourg Cathedral (France). We compared biological results to the age-at-death structure of the 1382 adults buried in the cathedral, calculated with historical sources from local death registers, and to a model life table specifically established for preindustrial populations. Results Cementochronology is reliable for estimating the mortality profile of young and middle adult age categories but underestimates older age categories. Discussion Taphonomy mainly explains the underestimation in elderly individuals. Although some issues remain to be addressedin order to properly implement the method and improve reliability, cementochronology makes a major contribution to palaeodemography, as it provides relatively reliable mortality profiles with a precision never attained before, thus offering new prospects for studying the mortality of past populations.

Background: One of the major causes of malaria-related deaths in Sub-Saharan African countries is the limited accessibility to quality care. In these countries, malaria control activities are implemented at the health district level. However, malaria indicators are often regionally representative. This paper provides an approach for estimating health district-level malaria readiness indicators from survey data designed to provide regionally representative estimates. Methods: A binomial hierarchical Bayesian spatial prediction method was applied to Service Availability and Readiness Assessment (SARA) survey data to provide estimates of essential equipment availability and readiness to provide malaria care at the health district level. Predicted values of each indicator were adjusted by the type of health facility, location, and population density. Then, a health district composite readiness profile was built via hierarchical ascendant classification. Results: All surveyed health-facilities were mandated to manage malaria. The spatial distribution of essential equipment and malaria readiness was heterogeneous. Around 62.9% of health districts had a high level of readiness to provide malaria care and prevention during pregnancy. Low-performance scores for managing malaria were found in big cities located in the central and Haut-Bassins regions. The health districts with low coverage for both first-line antimalarial drugs and rapid diagnostic tests were Baskuy, Bogodogo, Boulmiougou, Nongr-Massoum, Sig-Nonghin, Dafra, and Do. Conclusion: We provide health district estimates and reveal gaps in basic equipment and malaria management resources in some districts that need to be filled. By providing local-scale estimates, this approach could be replicated for other types of indicators to inform decision-makers and health program managers and to identify priority areas.

International audience; Purpose Coiling associated with placement of a self-expandable intracranial stent has improved the treatment of intracranial wide-necked aneurysms. Little is known, however, about the durability of this treatment. The purpose of this report is to present our experience with the LEO stent and to evaluate the complications, effectiveness, and long-term results of this technique. Methods We analyzed the records of 155 intracranial unruptured aneurysms that were treated by stent-assisted coiling with a LEO stent between 2008 and 2012. Procedural, early post-procedural, and delayed complications were recorded. Clinical and angiographic follow-up of patients was conducted over a period of at least 36 months. Results No procedural mortality was observed. One-month morbidity was observed in 14 out of 153 patients (9,15%). One hundred thirty-eight patients (with 140 aneurysms) had clinical and angiographic follow-up for more than 36 months. No aneurysm rupture was observed during follow-up. Four patients presented an intra-stent stenosis at 8 months, and 6 patients who had an early recurrence were retreated. Final results showed 85% complete occlusion, 13% neck remnants, and 2% stable incomplete occlusion. Conclusion Stent-assisted coiling with the LEO stent is a safe and effective treatment for unruptured intracranial aneurysms. The long-term clinical outcomes with the LEO stent are excellent with a high rate of complete occlusion that is stable over time.

Introduction Le Mali, comme beaucoup de pays d’Afrique sub-saharienne, n’a rapporté jusqu’à présent qu’un nombre limité de cas de COVID-19. Le nombre total de décès déclarés reste faible. En septembre 2020, on dénombrait 1532 cas et 81 décès sur la ville de Bamako, dont 466 cas et 27 décès dans la commune VI. Cette étude évalue la proportion de la population ayant été infectée par le SARS-CoV-2 à Bamako et la compare aux données rapportées afin d’éclairer l’épidémie de COVID-19 au Mali. Matériels et méthodes L’étude a eu lieu dans 3 quartiers de la commune VI de Bamako. Un échantillonnage stratifié par quartiers et secteurs a permis de tirer au sort des concessions, dans lesquelles tous les ménages acceptant de participer ont été inclus. Les participants ont été inclus à leur domicile, répondu à un questionnaire et fourni un échantillon sanguin. Les anticorps IgM et IgG contre la protéine Spike du SARS-CoV-2 ont été détectés par ELISA. La séroprévalence et l’intervalle de confiance à 95 % (IC95 %) ont été calculés pour la commune VI, par quartier, par classe d’âge. Le nombre total d’infections survenues à Bamako a été estimé en appliquant les taux de séroprévalence mesurés par âge et par sexe à la population de Bamako (données de recensement de 2009 actualisées en 2017). Le nombre de décès attendus a été calculé en appliquant aux infections estimées les taux de mortalité par classe d’âge observés en Chine durant la phase précoce de l’épidémie (alors que la prise en charge n’avait pas été optimisée). Résultats Du 16 au 29 septembre 2020, 1526 participants ont été inclus et 1367 résultats valides de sérologie obtenus. La séroprévalence brute s’élevait à 16,5 % (225/1367, IC95 % = 14,5–18,5 %). La prévalence était similaire entre les 3 quartiers (Chi2, p = 0,91). Une tendance non significative à l’augmentation avec l’âge a été observée. En tenant compte de la distribution par âge et par sexe de l’échantillon par rapport à celle de la population, la prévalence en population générale était estimée à 15,8 %, soit plus de 380 000 infections pour 2,4 millions d’habitants. Le nombre attendu de décès liés à la COVID-19 serait inférieur à 1500 entre mars et septembre 2020 à Bamako. Conclusion Cette étude transversale suggère une propagation lente mais généralisée du SARS-CoV-2 durant les 6 premiers mois de la pandémie à Bamako. La faible mortalité rapportée ne reflète pas les décès attendus, mais la létalité estimée reste faible (

Introduction Une plus forte transmissibilité du SARS-CoV-2 lorsque les conditions météorologiques sont plus froides et sèches a été envisagée dès le début de la pandémie, mais les démonstrations rigoureuses et la quantification de ces effets sont restées peu nombreuses. Matériels et méthodes Pendant la première vague de l’épidémie, l’Espagne, l’Italie, la France, le Portugal, le Canada et les États-Unis ont présenté une propagation précoce, une mortalité/morbidité élevée, et une réponse de santé publique initiale limitée, jusqu’à des mesures de confinement national ou régional. Dans un contexte où l’accès aux tests était limité, nous avons estimé le nombre de reproduction de base (R0) régional à partir de la croissance des nombres de décès quotidiens enregistrés tels que rapportés par les autorités sanitaires nationales. Les données météorologiques ont été extraites à partir des données mises à disposition par l’US National Oceanic and Atmospheric Administration via le package R {worldmet}. La relation entre R0 et les paramètres météorologiques a été analysée par un modèle généralisé additif (GAM) sous l’hypothèse d’une relation linéaire ou non linéaire (splines) en ajustant sur la densité de population, la proximité avec la première région touchée du pays et la proportion de personnes > 80 ans. Résultats Après exclusion des régions n’ayant pas présenté une phase de croissance exponentielle, 63 régions ont été analysées sur les 128 régions/états des 6 pays étudiés. Le R0 a été estimé sur une durée médiane de 11 jours (interquartile = 9–14). La valeur médiane de R0 était de 2,58 (interquartile = 2,08–2,66). L’humidité absolue médiane était de 4,98 g/m3 (min-max: 2,26, 11,32) et la température 9.8 °C (min-max: −2, 19,9). Dans le modèle multivarié, la température et l’humidité étaient négativement associées à la transmissibilité du SARS-CoV-2. Une diminution de 1 g/m3 était associée à une augmentation de 0,15 du R0 (p-value = 0,034, déviance expliquée 33,6 %). La température était également négativement associée au R0, mais avec une relation non linéaire : en dessous de 10 °C, la baisse d’1 °C de la température était associée à une augmentation de 0,16 du R0 (p-value = 0,00655, devance expliquée 41,5 %). Conclusion Nos résultats confirment que la transmissibilité du SARS-CoV-2 dépendait des conditions météorologiques/climatiques en l’absence de mesures de contrôle, durant la première vague, et quantifient cet écart. Il existait un écart de près d’une unité de R0 entre les régions ayant un climat hivernal doux (humidité ∼8 g/m3, températures ∼10 °C et plus) et celle ayant un climat rigoureux (humidité 3 g/m3, températures

Introduction Les facteurs meteorologiques et environnementaux, constituent des entraves dans la lutte contre le paludisme dans le Sahel a cause de son caractere instable. Au Nord du Mali, la transmission du paludisme varie d’une annee a l’autre caracterisee par des epidemies de temps en temps, tributaires de la pluviometrie. Le cercle de Bourem a enregistre une fluctuation des cas de paludisme de 2014-2018 dans un contexte de crise securitaire, socio-politique et d’ensablement du fleuve Niger. Cette etude avait pour objectif de determiner la contribution des facteurs meteorologique/environnementaux a la fluctuation des cas de paludisme dans le district sanitaire de Bourem de 2014 a 2018. Methodes Il s’agissait d’une analyse des donnees historiques hebdomadaires de 2014-2018, des etablissements de sante, des donnees de la hauteur du fleuve du service de l’hydraulique, et celles de la meteorologie collectees sur differents sites (MODDIS, AIRS). Une reduction de la dimension et des colinearites entre facteurs meteorologiques et environnementaux a ete realisee a l’aide d’une analyse en composante principale, permettant d’extraire des indicateurs synthetiques. L’evolution temporelle de l’incidence du paludisme et son association aux indicateurs synthetiques a ete analysee a l’aide d’un modele additif generalise. La recherche d’agregats spatiaux a ete realisee avec l’aide de la methode de balayage de Kulldorff. Resultats L’incidence du paludisme a montre une saisonnalite avec un pic significativement correle au mois de septembre (p 0,05). Les agregats de cas etaient situes au sud du cercle de Bourem et variaient dans le temps. Conclusion Cette etude a montre que le paludisme au nord du Mali varie en fonction de la pluviometrie, de l’humidite et de la temperature. Les activites de lutte, notamment la chimio-prevention saisonniere doivent etre focalisees sur le mois de septembre en priorisant les aires de sante du sud du cercle de Bourem situees le long du fleuve. Figure : http://extranet.insight-outside.fr/upload/compte1352/Base/inscriptions_projets/image/100169-image.pdf

Introduction L’identification de dynamiques temporelles locales de maladies infectieuses est un outil precieux pour decrire la transmission et guider le deploiement d’interventions differenciees. Ceci necessite la comparaison simultanee d’un grand nombre de series chronologiques. Ce travail propose une methodologie associant les donnees fonctionnelles a une classification de partitionnement autour des medoides (PAM), appliquee aux cas de paludisme a P. vivax (PV) dans une region du Myanmar ou l’incidence est fortement heterogene. Methodes Le taux d’incidence de PV a ete estime pour chaque village a partir des donnees de suivi des cas collectees dans le cadre d’un programme d’elimination du paludisme situe au Myanmar. Un lissage des series a ete realise par la transformation en donnees fonctionnelles grâce a l’analyse de regression penalisee sur la rugosite. Puis, une classification PAM a permis d’identifier des profils dynamiques parmi les series fonctionnelles. L’association de la classification PAM a une metrique flexible autorisant des decalages temporels dynamiques (DTW) a permis le regroupement de villages ayant des dynamiques saisonnieres similaires ne differant que par un decalage de quelques semaines. Resultats Au total, 657 series d’incidence de PV de 2016 a 2020 ont ete transformees en donnees fonctionnelles et classifiees en 10 profils dynamiques. Deux profils ne presentaient aucun cas de paludisme (n = 479), ou des cas sporadiques residuels (n = 77). Un profil se caracterisait par une tendance a la diminution de l’incidence en saison des pluies (n = 8), alors qu’un second se distinguait par l’apparition de cas uniquement en saison froide (n = 33). Deux profils presentaient une tendance a la hausse de l’incidence et se distinguaient par leur saisonnalite (n = 32, n = 18). Deux profils mettaient en evidence 8 villages ayant une incidence persistante. Enfin, deux profils identifiaient deux villages specifiques. Conclusion L’association de la classification PAM a la metrique DTW apres lissage en donnees fonctionnelles a permis de caracteriser des profils dynamiques selon leur saisonnalite, amplitude et tendance. Cette approche a mis en evidence 58 villages ayant une incidence persistante ou une tendance a l’augmentation. Ces villages constitueraient donc des lieux prioritaires d’intervention, notamment pour deployer l’acces au traitement radical de Plasmodium vivax.