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

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

Background In the last decade, an important scale-up was observed in malaria control interventions. Madagascar entered the process for pre-elimination in 2007. Policy making needs operational indicators, but also indicators about effectiveness and impact of malaria control interventions (MCI). This study is aimed at providing data about malaria infection, morbidity, and mortality, and MCI in Madagascar. Methods Two nationwide surveys were simultaneously conducted in 2012–2013 in Madagascar: a study about non-complicated clinical malaria cases in 31 sentinel health facilities, and a cross-sectional survey (CSS) in 62 sites. The CSS encompassed interviews, collection of biological samples and verbal autopsies (VA). Data from CSS were weighted for age, sex, malaria transmission pattern, and population density. VA data were processed with InterVA-4 software. Results CSS included 15,746 individuals of all ages. Parasite rate (PR) as measured by rapid diagnostic tests was 3.1%, and was significantly higher in five to 19 year olds, in males, poorer socio-economic status (SES) quintiles and rural areas. Long-lasting insecticidal nets (LLIN) use was 41.7% and was significantly lower in five to 19 year olds, males and wealthier SES quintiles. Proportion of persons covered by indoor residual spraying (IRS) was 66.8% in targeted zones. Proportion of persons using other insecticides than IRS was 22.8%. Coverage of intermittent preventive treatment during pregnancy was 21.5%. Exposure to information, education and communication messages about malaria was significantly higher in wealthier SES for all media but information meetings. The proportion of fever case managements considered as appropriate with regard to malaria was 15.8%. Malaria was attributed as the cause of death in 14.0% of 86 VA, and 50% of these deaths involved persons above the age of five years. The clinical case study included 818 cases of which people above the age of five accounted for 79.7%. In targeted zones, coverage of LLIN and IRS were lower in clinical cases than in general population. Conclusions This study provides valuable data for the evaluation of effectiveness and factors affecting MCI. MCI and evaluation surveys should consider the whole population and not only focus on under-fives and pregnant women in pre-elimination or elimination strategies. Electronic supplementary material The online version of this article (doi:10.1186/1475-2875-13-465) contains supplementary material, which is available to authorized users.

Background The health authorities of Niger have implemented several malaria prevention and control programmes in recent years. These interventions broadly follow WHO guidelines and international recommendations and are based on interventions that have proved successful in other parts of Africa. Most performance indicators are satisfactory but, paradoxically, despite the mobilization of considerable human and financial resources, the malaria-fighting programme in Niger seems to have stalled, as it has not yet yielded the expected significant decrease in malaria burden. Indeed, the number of malaria cases reported by the National Health Information System has actually increased by a factor of five over the last decade, from about 600,000 in 2000 to about 3,000,000 in 2010. One of the weaknesses of the national reporting system is that the recording of malaria cases is still based on a presumptive diagnosis approach, which overestimates malaria incidence. Methods An extensive nationwide survey was carried out to determine by microscopy and RDT testing, the proportion of febrile patients consulting at health facilities for suspected malaria actually suffering from the disease, as a means of assessing the magnitude of this problem and obtaining a better estimate of malaria morbidity in Niger. Results In total, 12,576 febrile patients were included in this study; 57% of the slides analysed were positive for the malaria parasite during the rainy season, when transmission rates are high, and 9% of the slides analysed were positive during the dry season, when transmission rates are lower. The replacement of microscopy methods by rapid diagnostic tests resulted in an even lower rate of confirmation, with only 42% of cases testing positive during the rainy season, and 4% during the dry season. Fever alone has a low predictive value, with a low specificity and sensitivity. These data highlight the absolute necessity of confirming all reported malaria cases by biological diagnosis methods, to increase the accuracy of the malaria indicators used in monitoring and evaluation processes and to improve patient care in the more remote areas of Niger. This country extends over a large range of latitudes, resulting in the existence of three major bioclimatic zones determining vector distribution and endemicity. Conclusion This survey showed that the number of cases of presumed malaria reported in health centres in Niger is largely overestimated. The results highlight inadequacies in the description of the malaria situation and disease risk in Niger, due to the over-diagnosis of malaria in patients with simple febrile illness. They point out the necessity of confirming all cases of suspected malaria by biological diagnosis methods and the need to take geographic constraints into account more effectively, to improve malaria control and to adapt the choice of diagnostic method to the epidemiological situation in the area concerned. Case confirmation will thus also require a change in behaviour, through the training of healthcare staff, the introduction of quality control, greater supervision of the integrated health centres, the implementation of good clinical practice and a general optimization of the use of available diagnostic methods.

Background Meningococcal meningitis is a major health problem in the “African Meningitis Belt” where recurrent epidemics occur during the hot, dry season. In Niger, a central country belonging to the Meningitis Belt, reported meningitis cases varied between 1,000 and 13,000 from 2003 to 2009, with a case-fatality rate of 5–15%. Methodology/Principal Findings In order to gain insight in the epidemiology of meningococcal meningitis in Niger and to improve control strategies, the emergence of the epidemics and their diffusion patterns at a fine spatial scale have been investigated. A statistical analysis of the spatio-temporal distribution of confirmed meningococcal meningitis cases was performed between 2002 and 2009, based on health centre catchment areas (HCCAs) as spatial units. Anselin's local Moran's I test for spatial autocorrelation and Kulldorff's spatial scan statistic were used to identify spatial and spatio-temporal clusters of cases. Spatial clusters were detected every year and most frequently occurred within nine southern districts. Clusters most often encompassed few HCCAs within a district, without expanding to the entire district. Besides, strong intra-district heterogeneity and inter-annual variability in the spatio-temporal epidemic patterns were observed. To further investigate the benefit of using a finer spatial scale for surveillance and disease control, we compared timeliness of epidemic detection at the HCCA level versus district level and showed that a decision based on threshold estimated at the HCCA level may lead to earlier detection of outbreaks. Conclusions/Significance Our findings provide an evidence-based approach to improve control of meningitis in sub-Saharan Africa. First, they can assist public health authorities in Niger to better adjust allocation of resources (antibiotics, rapid diagnostic tests and medical staff). Then, this spatio-temporal analysis showed that surveillance at a finer spatial scale (HCCA) would be more efficient for public health response: outbreaks would be detected earlier and reactive vaccination would be better targeted., Author Summary Meningococcal meningitis (MM) is an infection of the meninges caused by a bacterium, Neisseria meningitidis, transmitted through respiratory and throat secretions. It can cause brain damage and results in death in 5–15% of cases. Large epidemics of MM occur almost every year in sub-Saharan Africa during the hot, dry season. Understanding how epidemics emerge and spread in time and space would help public health authorities to develop more efficient strategies for the prevention and the control of meningitis. We studied the spatio-temporal distribution of MM cases in Niger from 2002 to 2009 at the scale of the health centre catchment areas (HCCAs). We found that spatial clusters of cases most frequently occurred within nine districts out of 42, which can assist public health authorities to better adjust allocation of resources such as antibiotics or rapid diagnostic tests. We also showed that the epidemics break out in different HCCAs from year to year and did not follow a systematic geographical direction. Finally, this analysis showed that surveillance at a finer spatial scale (health centre catchment area rather than district) would be more efficient for public health response: outbreaks would be detected earlier and reactive vaccination would be better targeted.

International audience; Malaria elimination, one of the Sustainable Development Goals of the United Nation, is challenged by cross-border context specificities. At the French Guiana-Brazil border, a system was developed to harmonized epidemiological data providing by the two countries. This study evaluates the feasibility of using such harmonized data to build a cross-border early warning system. To this end, the study compared ARI-MAX and LSTM approaches. Time-lagged meteorological data were introduced to improve the forecasts. LSTM outperformed ARIMAX, with a 10 to 39% decrease of Mean Absolute and Root Means Square Errors, and better predicted low case numbers. Meteorological data improved significantly model predictions, by considering time-lags from 3 to 7 weeks compatible with the knowledge found in the literature. This study demonstrated the feasibility of building a cross-border malaria early warning system, that would significantly contribute to malaria control and elimination.