Analysing spatio-temporal clustering of meningococcal meningitis outbreaks in Niger reveals opportunities for improved disease control

Meningitis in Niger Republic amidst COVID-19: current issues and novel recommendations

Amidst coronavirus disease 2019 (COVID-19), there has been a misplaced priority on meningitis in the Niger Republic, thus refocusing resources and attention away from the continuing meningitis campaign in the Niger Republic. The over-strained state of public health resources and staff has also led to decreased surveillance, postponed diagnoses, and constrained immunization efforts in Niger Republic. This review aims to bridge the gaps regarding meningitis amid COVID-19 in Niger Republic and offer recommendations to government to mitigate meningitis in the country, with the hope of finding a permanent solution to this debilitating disease. The authors reviewed 45 past and present pieces of literature on meningitis and COVID-19 from 2013 to 2023 in well-renowned scientific databases such as PubMed, ResearchGate, Google Scholar, African Journals Online, Medline, and Embase. Since 2015, Niger Republic has experienced multiple meningitis epidemics that have resulted in 20, 789 cases and 1, 369 deaths [a case fatality rate (CFR) of 6.6%]. A total of 231 cases of meningitis were reported from 1 November 2021 to 31 January 2022. And recently, 559 cases of meningitis (of which 111 are laboratory confirmed), including 18 deaths (overall CFR 3.2%), occurred in the Zinder region, southeast of Niger Republic, from 1 November 2022 to 27 January 2023. Meningitis remains a public health concern in the world, especially in Niger Republic, which could lead to serious long-term complications. Therefore, adequate and novel measures and therapeutic actions should be implemented by the Niger Government to lessen the burden of the disease in the country.

High-spatial resolution epidemic surveillance of bacterial meningitis in the African meningitis belt in Burkina Faso

Despite improved surveillance capacities and WHO recommendations for subdistrict analysis, routine epidemic surveillance of acute bacterial meningitis in the African meningitis belt remains largely limited to the district level. We evaluated the appropriateness and performance of analyses at higher spatial resolution. We used suspected meningitis surveillance data at health centre (HC) resolution from Burkina Faso from 14 health districts spanning years 2004-2014 and analysed them using spatio-temporal statistics and generative models. An operational analysis compared epidemic signals at district and HC-level using weekly incidence thresholds. Eighty-four percent (N = 98/116) of epidemic clusters spanned only one HC-week. Spatial propagation of epidemic clusters was mostly limited to 10-30 km. During the 2004-2009 (with serogroup A meningitis) and 2010-2014 (after serogroup A elimination) period, using weekly HC-level incidence thresholds of 100 and 50 per 100,000 respectively, we found a gain in epidemic detection and timeliness in 9 (41% of total) and 10 (67%), respectively, district years with at least one HC signal. Individual meningitis epidemics expanded little in space, suggesting that a health centre level analysis is most appropriate for epidemic surveillance. Epidemic surveillance could gain in precision and timeliness by higher spatial resolution. The optimal threshold should be defined depending on the current background incidence of bacterial meningitis.

Spatial epidemiology of bacterial meningitis in the Upper West Region of Ghana: Analysis of disease surveillance data 2018-2020

Background

The use of a Geographic Information System in identifying meningitis hotspots in the Upper West Region (UWR) remains underutilized, making spatial targeting of meningitis hotspots difficult. We therefore utilized surveillance data enabled with GIS technology to target meningitis outbreaks in the UWR.

Methods

Secondary data analysis was conducted in the study. The dynamics of bacterial meningitis in space and time were studied using epidemiological data from 2018 to 2020. Spot map and choropleths were used to depict the distribution of cases in the region. Moran's I statistics were used to assess spatial autocorrelation. Getis-Ord Gi*(d) and Anselin Local Moran's statistics were used to identify hotspots and spatial outliers within the study area. A Geographic Weighted Regression model was also used to examine how socio bio-climatic conditions influence the spread of meningitis.

Results

There were 1176 cases of bacterial meningitis, 118 deaths, and 1058 survivors between 2018 and 2020. Nandom municipality had the highest Attack Rate (AR) at 492/100,000 persons, followed by Nadowli-Kaleo district at 314/100,000 persons. Jirapa had the highest case fatality rate (CFR) at 17%. The spatio-temporal analysis showed spatial diffusion of meningitis prevalence from the western half of the UWR to the east with a significant number of hotpots and cluster outliers.

Conclusion

Bacterial meningitis does not occur at random. Populations (10.9%) under sub-districts identified as hotspots are exceptionally at higher risk of outbreaks. Targeted interventions should be directed towards clustered hotspots, focusing on zones with low prevalence fenced off by high prevalence zones.

Efficiency of fine scale and spatial regression in modelling associations between healthcare service spatial accessibility and their utilization

BACKGROUND

Healthcare accessibility, a key public health issue, includes potential (spatial accessibility) and realized access (healthcare utilization) dimensions. Moreover, the assessment of healthcare service potential access and utilization should take into account the care provided by primary and secondary services. Previous studies on the relationship between healthcare spatial accessibility and utilization often used conventional statistical methods without addressing the scale effect and spatial processes. This study investigated the impact of spatial accessibility to primary and secondary healthcare services on length of hospital stay (LOS), and the efficiency of using a geospatial approach to model this relationship.

METHODS

This study focused on the ≥ 75-year-old population of the Nord administrative region of France. Inpatient hospital spatial accessibility was computed with the E2SFCA method, and then the LOS was calculated from the French national hospital activity and patient discharge database. Ordinary least squares (OLS), spatial autoregressive (SAR), and geographically weighted regression (GWR) were used to analyse the relationship between LOS and spatial accessibility to inpatient hospital care and to three primary care service types (general practitioners, physiotherapists, and home-visiting nurses). Each model performance was assessed with measures of goodness of fit. Spatial statistical methods to reduce or eliminate spatial autocorrelation in the residuals were also explored.

RESULTS

GWR performed best (highest R2 and lowest Akaike information criterion). Depending on global model (OLS and SAR), LOS was negatively associated with spatial accessibility to general practitioners and physiotherapists. GWR highlighted local patterns of spatial variation in LOS estimates. The distribution of areas in which LOS was positively or negatively associated with spatial accessibility varied when considering accessibility to general practitioners and physiotherapists.

CONCLUSIONS

Our findings suggest that spatial regressions could be useful for analysing the relationship between healthcare spatial accessibility and utilization. In our case study, hospitalization of elderly people was shorter in areas with better accessibility to general practitioners and physiotherapists. This may be related to the presence of effective community healthcare services. GWR performed better than LOS and SAR. The identification by GWR of how these relationships vary spatially could bring important information for public healthcare policies, hospital decision-making, and healthcare resource allocation.

Spatial-temporal patterns of malaria incidence in Uganda using HMIS data from 2015 to 2019

BACKGROUND

As global progress to reduce malaria transmission continues, it is increasingly important to track changes in malaria incidence rather than prevalence. Risk estimates for Africa have largely underutilized available health management information systems (HMIS) data to monitor trends. This study uses national HMIS data, together with environmental and geographical data, to assess spatial-temporal patterns of malaria incidence at facility catchment level in Uganda, over a recent 5-year period.

METHODS

Data reported by 3446 health facilities in Uganda, between July 2015 and September 2019, was analysed. To assess the geographic accessibility of the health facilities network, AccessMod was employed to determine a three-hour cost-distance catchment around each facility. Using confirmed malaria cases and total catchment population by facility, an ecological Bayesian conditional autoregressive spatial-temporal Poisson model was fitted to generate monthly posterior incidence rate estimates, adjusted for caregiver education, rainfall, land surface temperature, night-time light (an indicator of urbanicity), and vegetation index.

RESULTS

An estimated 38.8 million (95% Credible Interval [CI]: 37.9-40.9) confirmed cases of malaria occurred over the period, with a national mean monthly incidence rate of 20.4 (95% CI: 19.9-21.5) cases per 1000, ranging from 8.9 (95% CI: 8.7-9.4) to 36.6 (95% CI: 35.7-38.5) across the study period. Strong seasonality was observed, with June-July experiencing highest peaks and February-March the lowest peaks. There was also considerable geographic heterogeneity in incidence, with health facility catchment relative risk during peak transmission months ranging from 0 to 50.5 (95% CI: 49.0-50.8) times higher than national average. Both districts and health facility catchments showed significant positive spatial autocorrelation; health facility catchments had global Moran's I = 0.3 (p < 0.001) and districts Moran's I = 0.4 (p < 0.001). Notably, significant clusters of high-risk health facility catchments were concentrated in Acholi, West Nile, Karamoja, and East Central - Busoga regions.

CONCLUSION

Findings showed clear countrywide spatial-temporal patterns with clustering of malaria risk across districts and health facility catchments within high risk regions, which can facilitate targeting of interventions to those areas at highest risk. Moreover, despite high and perennial transmission, seasonality for malaria incidence highlights the potential for optimal and timely implementation of targeted interventions.

The environmental drivers of bacterial meningitis epidemics in the Democratic Republic of Congo, central Africa

INTRODUCTION

Bacterial meningitis still constitutes an important threat in Africa. In the meningitis belt, a clear seasonal pattern in the incidence of meningococcal disease during the dry season has been previously correlated with several environmental parameters like dust and sand particles as well as the Harmattan winds. In parallel, the evidence of seasonality in meningitis dynamics and its environmental variables remain poorly studied outside the meningitis belt. This study explores several environmental factors associated with meningitis cases in the Democratic Republic of Congo (DRC), central Africa, outside the meningitis belt area.

METHODS

Non-parametric Kruskal-Wallis' tests were used to establish the difference between the different health zones, climate and vegetation types in relation to both the number of cases and attack rates for the period 2000-2018. The relationships between the number of meningitis cases for the different health zones and environmental and socio-economical parameters collected were modeled using different generalized linear (GLMs) and generalized linear mixed models (GLMMs), and different error structure in the different models, i.e., Poisson, binomial negative, zero-inflated binomial negative and more elaborated multi-hierarchical zero-inflated binomial negative models, with randomization of certain parameters or factors (health zones, vegetation and climate types). Comparing the different statistical models, the model with the smallest Akaike's information criterion (AIC) were selected as the best ones. 515 different health zones from 26 distinct provinces were considered for the construction of the different GLM and GLMM models.

RESULTS

Non-parametric bivariate statistics showed that there were more meningitis cases in urban health zones than in rural conditions (χ2 = 6.910, p-value = 0.009), in areas dominated by savannah landscape than in areas with dense forest or forest in mountainous areas (χ2 = 15.185, p-value = 0.001), and with no significant difference between climate types (χ2 = 1.211, p-value = 0,449). Additionally, no significant difference was observed for attack rate between the two types of heath zones (χ2 = 0.982, p-value = 0.322). Conversely, strong differences in attack rate values were obtained for vegetation types (χ2 = 13.627, p-value = 0,001) and climate types (χ2 = 13.627, p-value = 0,001). This work demonstrates that, all other parameters kept constant, an urban health zone located at high latitude and longitude eastwards, located at low-altitude like in valley ecosystems predominantly covered by savannah biome, with a humid tropical climate are at higher risk for the development of meningitis. In addition, the regions with mean range temperature and a population with a low index of economic well-being (IEW) constitute the perfect conditions for the development of meningitis in DRC.

CONCLUSION

In a context of global environmental change, particularly climate change, our findings tend to show that an interplay of different environmental and socio-economic drivers are important to consider in the epidemiology of bacterial meningitis epidemics in DRC. This information is important to help improving meningitis control strategies in a large country located outside of the so-called meningitis belt.

Geospatial clustering of meningitis: an early warning system (hotspot) for potential meningitis outbreak in upper east region of Ghana

OBJECTIVE

We mapped and generated hot spots for potential meningitis outbreak from existing data in Upper East region, Ghana.

DESIGN

This was a cross-sectional study conducted in 2017.

DATA SOURCE

Meningitis data in the Upper East Region from January 2007, to December 2016.

MAIN OUTCOME MEASURE

We used spatial tools in Quantum Geographic Information System (QGIS) and Geoda to draw choropleth map of meningitis incidence, case fatality and hotspot for potential meningitis outbreak.

RESULTS

A total of 2312 meningitis cases (suspected and confirmed) were recorded from 2016-2017 with median incidence of 15.0cases/100,000 population (min 6.3, max 47.8). Median age of cases was 15 years (IQR: 6-31 years). Most (44.2%) of those affected were 10 years and below. Females (51.2%) constituted the highest proportion. Median incidence from 2007-2011 was 20cases/100,000 population (Min 11.3, Max 39.9) whilst from 2012-2016 was 11.1cases/100,000 populations (Min 6.3, Max 47.8). A total of 28 significant hotspot sub-districts clusters (p=0.024) were identified with 7 High-high risk areas as potential meningitis outbreak spots.

CONCLUSION

The occurrence of meningitis is not random, spatial cluster with high -high-risk exist in some sub-districts. Overall meningitis incidence and fatality rate have declined in the region with district variations. Districts with high meningitis incidence and fatality rates should be targeted for intervention.

FUNDING

Author EA was supported by the West Africa Health Organization (Ref.: Prog/A17IEpidemSurveillN°57212014/mcrt).

Mathematical modeling and analysis of meningococcal meningitis transmission dynamics

Meningococcal meningitis (MCM) is one of the serious public health threats in the tropical and sub-tropical regions. In this paper, we propose an epidemic model to study the transmission dynamics of MCM with high- and low-risk susceptible populations. The model considers two different groups of susceptible individuals depending on the availability of medical resources (MR, including hospitals, health workers, etc.), which varies the infection risk. We find that the model exhibits the phenomenon of backward bifurcation (BB), which increases the difficulty of MCM control since the dynamics are not merely relying on the basic reproduction number, [Formula: see text]. This study explores the effects of MR on the MCM epidemics by mathematical analysis and shows the existence of BB on MCM disease. Our findings suggest that providing adequate MR in a community is crucial in mitigating MCM incidences and deaths, especially, in the MCM endemic regions.

Spatiotemporal Analysis of Serogroup C Meningococcal Meningitis Spread in Niger and Nigeria and Implications for Epidemic Response

BACKGROUND

After the re-emergence of serogroup C meningococcal meningitis (MM) in Nigeria and Niger, we aimed to re-evaluate the vaccination policy used to respond to outbreaks of MM in the African meningitis belt by investigating alternative strategies using a lower incidence threshold and information about neighboring districts.

METHODS

We used data on suspected and laboratory-confirmed cases in Niger and Nigeria from 2013 to 2017. We calculated global and local Moran's I-statistics to identify spatial clustering of districts with high MM incidence. We used a Pinner model to estimate the impact of vaccination campaigns occurring between 2015 and 2017 and to evaluate the impact of 3 alternative district-level vaccination strategies, compared with that currently used.

RESULTS

We found significant clustering of high incidence districts in every year, with local clusters around Tambuwal, Nigeria in 2013 and 2014, Niamey, Niger in 2016, and in Sokoto and Zamfara States in Nigeria in 2017.We estimate that the vaccination campaigns implemented in 2015, 2016, and 2017 prevented 6% of MM cases. Using the current strategy but with high coverage (85%) and timely distribution (4 weeks), these campaigns could have prevented 10% of cases. This strategy required the fewest doses of vaccine to prevent a case. None of the alternative strategies we evaluated were more efficient, but they would have prevented the occurrence of more cases overall.

CONCLUSIONS

Although we observed significant spatial clustering in MM in Nigeria and Niger between 2013 and 2017, there is no strong evidence to support a change in methods for epidemic response in terms of lowering the intervention threshold or targeting neighboring districts for reactive vaccination.

Analysis of a meningococcal meningitis outbreak in Niger - potential effectiveness of reactive prophylaxis

Background

Seasonal epidemics of bacterial meningitis in the African Meningitis Belt carry a high burden of disease and mortality. Reactive mass vaccination is used as a control measure during epidemics, but the time taken to gain immunity from the vaccine reduces the flexibility and effectiveness of these campaigns. Targeted reactive antibiotic prophylaxis could be used to supplement reactive mass vaccination and further reduce the incidence of meningitis, and the potential effectiveness and efficiency of these strategies should be explored.

Methods and findings

Data from an outbreak of meningococcal meningitis in Niger, caused primarily by Neisseria meningitidis serogroup C, is used to estimate clustering of meningitis cases at the household and village level. In addition, reactive antibiotic prophylaxis and reactive vaccination strategies are simulated to estimate their potential effectiveness and efficiency, with a focus on the threshold and spatial unit used to declare an epidemic and initiate the intervention.

There is village-level clustering of suspected meningitis cases after an epidemic has been declared in a health area. Risk of suspected meningitis among household contacts of a suspected meningitis case is no higher than among members of the same village. Village-wide antibiotic prophylaxis can target subsequent cases in villages: across of range of parameters pertaining to how the intervention is performed, up to 220/672 suspected cases during the season are potentially preventable. On the other hand, household prophylaxis targets very few cases. In general, the village-wide strategy is not very sensitive to the method used to declare an epidemic. Finally, village-wide antibiotic prophylaxis is potentially more efficient than mass vaccination of all individuals at the beginning of the season, and than the equivalent reactive vaccination strategy.

Conclusions

Village-wide antibiotic prophylaxis should be considered and tested further as a response against outbreaks of meningococcal meningitis in the Meningitis Belt, as a supplement to reactive mass vaccination.

Until a low-cost polyvalent conjugate meningococcal vaccine becomes available in the African Meningitis Belt, reactive strategies to control meningitis epidemics should be considered and tested, and refined in order to maximise effectiveness. A recent cluster-randomised trial conducted in Niger showed promising evidence for the effectiveness of a village-wide reactive antibiotic prophylaxis intervention. We used data from a meningitis outbreak in Niger to explore the potential effectiveness and efficiency of this and other strategies when deployed on a wider scale, allowing us to compare different strategies without recourse to additional randomised trials. This study provided further evidence that village-wide antibiotic prophylaxis targets subsequent cases in villages, and showed that the intervention remains effective whether it is initiated early in the season (targeting more cases during the season) or later (when clustering of cases by village is strongest). For this outbreak, reactive village-wide antibiotic prophylaxis would have been more potentially efficient than mass vaccination at the beginning of the season, implying that targeted prophylaxis could supplement reactive mass vaccination. Many authors have developed models for vaccination strategies to reduce the burden of meningitis in sub-Saharan Africa; our results add to this literature by considering antibiotic prophylaxis as an intervention.

Compartmental models for seasonal hyperendemic bacterial meningitis in the African meningitis belt

The pathophysiological mechanisms underlying the seasonal dynamic and epidemic occurrence of bacterial meningitis in the African meningitis belt remain unknown. Regular seasonality (seasonal hyperendemicity) is observed for both meningococcal and pneumococcal meningitis and understanding this is critical for better prevention and modelling. The two principal hypotheses for hyperendemicity during the dry season imply (1) an increased risk of invasive disease given asymptomatic carriage of meningococci and pneumococci; or (2) an increased transmission of these bacteria from carriers and ill individuals. In this study, we formulated three compartmental deterministic models of seasonal hyperendemicity, featuring one (model1-'inv' or model2-'transm'), or a combination (model3-'inv-transm') of the two hypotheses. We parameterised the models based on current knowledge on meningococcal and pneumococcal biology and pathophysiology. We compared the three models' performance in reproducing weekly incidences of suspected cases of acute bacterial meningitis reported by health centres in Burkina Faso during 2004-2010, through the meningitis surveillance system. The three models performed well (coefficient of determination R2, 0.72, 0.86 and 0.87, respectively). Model2-'transm' and model3-'inv-transm' better captured the amplitude of the seasonal incidence. However, model2-'transm' required a higher constant invasion rate for a similar average baseline transmission rate. The results suggest that a combination of seasonal changes of the risk of invasive disease and carriage transmission is involved in the hyperendemic seasonality of bacterial meningitis in the African meningitis belt. Consequently, both interventions reducing the risk of nasopharyngeal invasion and the bacteria transmission, especially during the dry season are believed to be needed to limit the recurrent seasonality of bacterial meningitis in the meningitis belt.

Time delays in the response to the Neisseria meningitidis serogroup C outbreak in Nigeria - 2017

Background

Nigeria reports high rates of mortality linked with recurring meningococcal meningitis outbreaks within the African meningitis belt. Few studies have thoroughly described the response to these outbreaks to provide strong and actionable public health messages. We describe how time delays affected the response to the 2016/2017 meningococcal meningitis outbreak in Nigeria.

Methods

Using data from Nigeria Centre for Disease Control (NCDC), National Primary Health Care Development Agency (NPHCDA), World Health Organisation (WHO), and situation reports of rapid response teams, we calculated attack and death rates of reported suspected meningococcal meningitis cases per week in Zamfara, Sokoto and Yobe states respectively, between epidemiological week 49 in 2016 and epidemiological week 25 in 2017. We identified when alert and epidemic thresholds were crossed and determined when the outbreak was detected and notified in each state. We examined response activities to the outbreak.

Results

There were 12,535 suspected meningococcal meningitis cases and 877 deaths (CFR: 7.0%) in the three states. It took an average time of three weeks before the outbreaks were detected and notified to NCDC. Four weeks after receiving notification, an integrated response coordinating centre was set up by NCDC and requests for vaccines were sent to International Coordinating Group (ICG) on vaccine provision. While it took ICG one week to approve the requests, it took an average of two weeks for approximately 41% of requested vaccines to arrive. On the average, it took nine weeks from the date the epidemic threshold was crossed to commencement of reactive vaccination in the three states.

Conclusion

There were delays in detection and notification of the outbreak, in coordinating response activities, in requesting for vaccines and their arrival from ICG, and in initiating reactive vaccination. Reducing these delays in future outbreaks could help decrease the morbidity and mortality linked with meningococcal meningitis outbreaks.

Evaluation of response strategies against epidemics due to Neisseria meningitidis C in Niger

OBJECTIVE

To inform public health recommendations, we evaluated the effectiveness and efficiency of current and hypothetical surveillance and vaccine response strategies against Neisseria meningitidis C meningitis epidemics in 2015 in Niger.

METHODS

We analysed reports of suspected and confirmed cases of meningitis from the region of Dosso during 2014 and 2015. Based on a definition of epidemic signals, the effectiveness and efficiency of surveillance and vaccine response strategies were evaluated by calculating the number of potentially vaccine-preventable cases and number of vaccine doses needed per epidemic signal.

RESULTS

A total of 4763 weekly health area reports, collected in 90 health areas with 1282 suspected meningitis cases, were included. At a threshold of 10 per 100 000, the total number of estimated vaccine-preventable cases was 29 with district-level surveillance and vaccine response, 141 with health area-level surveillance and vaccination and 339 with health area-level surveillance and district-level vaccination. While being most effective, the latter strategy required the largest number of vaccine doses (1.8 million), similar to the strategy of surveillance and vaccination at district level (1.3 million), whereas the strategy of surveillance and vaccination at health area level would have required only 0.8 million doses. Thus, efficiency was lowest for district-level surveillance and highest for health area-level surveillance with district-level vaccination.

CONCLUSION

In this analysis, we found that effectiveness and efficiency were higher at health area-level surveillance and district-level vaccination than for other strategies. Use of N. meningitidis C vaccines in a preventive strategy thus should be considered, in particular as most reactive vaccine response strategies in our analysis had little impact on disease burden.

Towards understanding the epidemiology of Neisseria meningitidis in the African meningitis belt: a multi-disciplinary overview

OBJECTIVES

Neisseria meningitidis is the major cause of seasonal meningitis epidemics in the African meningitis belt. In the changing context of a reduction in incidence of serogroup A and an increase in incidence of serogroups W and C and of Streptococcus pneumoniae, a better understanding of the determinants driving the disease transmission dynamics remains crucial to improving bacterial meningitis control.

METHODS

The literature was searched to provide a multi-disciplinary overview of the determinants of meningitis transmission dynamics in the African meningitis belt.

RESULTS

Seasonal hyperendemicity is likely predominantly caused by increased invasion rates, sporadic localized epidemics by increased transmission rates, and larger pluri-annual epidemic waves by changing population immunity. Carriage likely involves competition for colonization and cross-immunity. The duration of immunity likely depends on the acquisition type. Major risk factors include dust and low humidity, and presumably human contact rates and co-infections; social studies highlighted environmental and dietary factors, with supernatural explanations.

CONCLUSIONS

Efforts should focus on implementing multi-country, longitudinal seroprevalence and epidemiological studies, validating immune markers of protection, and improving surveillance, including more systematic molecular characterizations of the bacteria. Integrating climate and social factors into disease control strategies represents a high priority for optimizing the public health response and anticipating the geographic evolution of the African meningitis belt.

Serogroup-Specific Characteristics of Localized Meningococcal Meningitis Epidemics in Niger 2002-2012 and 2015: Analysis of Health Center Level Surveillance Data

To compare dynamics of localized meningitis epidemics (LE) by meningococcal (Nm) serogroup, we analyzed a surveillance database of suspected and laboratory-confirmed Nm cases from 373 health areas (HA) of three regions in Niger during 2002-2012 and one region concerned by NmC epidemics during 2015. We defined LE as HA weekly incidence rates of ≥20 suspected cases per 100,000 during ≥2 weeks and assigned the predominant serogroup based on polymerase chain reaction testing of cerebrospinal fluid. Among the 175 LE, median peak weekly incidence rate in LE due to NmA, W, X and C were 54, 39, 109 and 46 per 100,000, respectively. These differences impacted ability of the epidemic to be detected at the district level. While this analysis is limited by the small number of LE due to NmX (N = 4) and NmW (N = 5), further research should explore whether strategies for prevention and response to meningitis epidemics need to be adapted according to predominant meningococcal serogroups.

Serogroup W Meningitis Outbreak at the Subdistrict Level, Burkina Faso, 2012

In 2012, Neisseria meningitidis serogroup W caused a widespread meningitis epidemic in Burkina Faso. We describe the dynamic of the epidemic at the subdistrict level. Disease detection at this scale allows for a timelier response, which is critical in the new epidemiologic landscape created in Africa by the N. meningitidis A conjugate vaccine.

Response Strategies against Meningitis Epidemics after Elimination of Serogroup A Meningococci, Niger

Surveillance and epidemic vaccine response would be most effective at the health area level.

To inform epidemic response strategies for the African meningitis belt after a meningococcal serogroup A conjugate vaccine was introduced in 2010, we compared the effectiveness and efficiency of meningitis surveillance and vaccine response strategies at district and health area levels using various thresholds of weekly incidence rates. We analyzed reports of suspected cases from 3 regions in Niger during 2002–2012 (154,392 health area weeks), simulating elimination of serogroup A meningitis by excluding health area years with identification of such cases. Effectiveness was highest for health area surveillance and district vaccination (58–366 cases; thresholds 7–20 cases/100,000 doses), whereas efficiency was optimized with health area vaccination (5.6–7.7 cases/100,000 doses). District-level intervention prevented <6 cases (0.2 cases/100,000 doses). Reducing the delay between epidemic signal and vaccine protection by 2 weeks doubled efficiency. Subdistrict surveillance and response might be most appropriate for meningitis epidemic response after elimination of serogroup A meningitis.

Identifying Spatial Clusters of Schistosomiasis in Anhui Province of China: A Study from the Perspective of Application

With the strategy shifting from morbidity control to transmission interruption, the burden of schistosomiasis in China has been declining over the past decade. However, further controls of the epidemic in the lake and marshland regions remain a challenge. Prevalence data at county level were obtained from the provincial surveillance system in Anhui during 1997–2010. Spatial autocorrelation analysis and spatial scan statistics were combined to assess the spatial pattern of schistosomiasis. The spatial-temporal cluster analysis based on retrospective space-time scan statistics was further used to detect risk clusters. The Global Moran’s I coefficients were mostly statistically significant during 1997–2004 but not significant during 2005–2010. The clusters detected by two spatial cluster methods occurred in Nanling, Tongling, Qingyang and Wuhu during 1997–2004, and Guichi and Wuhu from 2005 to 2010, respectively. Spatial-temporal cluster analysis revealed 2 main clusters, namely Nanling (1999–2002) and Guichi (2005–2008). The clustering regions were significantly narrowed while the spatial extent became scattered during the study period. The high-risk areas shifted from the low reaches of the Yangtze River to the upper stream, suggesting the focus of schistosomiasis control should be shifted accordingly and priority should be given to the snail habitats within the high-risk areas of schistosomiasis.

Soil dust aerosols and wind as predictors of seasonal meningitis incidence in Niger

BACKGROUND

Epidemics of meningococcal meningitis are concentrated in sub-Saharan Africa during the dry season, a period when the region is affected by the Harmattan, a dry and dusty northeasterly trade wind blowing from the Sahara into the Gulf of Guinea.

OBJECTIVES

We examined the potential of climate-based statistical forecasting models to predict seasonal incidence of meningitis in Niger at both the national and district levels.

DATA AND METHODS

We used time series of meningitis incidence from 1986 through 2006 for 38 districts in Niger. We tested models based on data that would be readily available in an operational framework, such as climate and dust, population, and the incidence of early cases before the onset of the meningitis season in January-May. Incidence was used as a proxy for immunological state, susceptibility, and carriage in the population. We compared a range of negative binomial generalized linear models fitted to the meningitis data.

RESULTS

At the national level, a model using early incidence in December and averaged November-December zonal wind provided the best fit (pseudo-R2 = 0.57), with zonal wind having the greatest impact. A model with surface dust concentration as a predictive variable performed indistinguishably well. At the district level, the best spatiotemporal model included zonal wind, dust concentration, early incidence in December, and population density (pseudo-R2 = 0.41).

CONCLUSIONS

We showed that wind and dust information and incidence in the early dry season predict part of the year-to-year variability of the seasonal incidence of meningitis at both national and district levels in Niger. Models of this form could provide an early-season alert that wind, dust, and other conditions are potentially conducive to an epidemic.

Spatio-temporal patterns of schistosomiasis japonica in lake and marshland areas in China: the effect of snail habitats

The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004-2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004-2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future.

Spatio-temporal factors associated with meningococcal meningitis annual incidence at the health centre level in Niger, 2004-2010

BACKGROUND

Epidemics of meningococcal meningitis (MM) recurrently strike the African Meningitis Belt. This study aimed at investigating factors, still poorly understood, that influence annual incidence of MM serogroup A, the main etiologic agent over 2004-2010, at a fine spatial scale in Niger.

METHODOLOGY/PRINCIPAL FINDINGS

To take into account data dependencies over space and time and control for unobserved confounding factors, we developed an explanatory Bayesian hierarchical model over 2004-2010 at the health centre catchment area (HCCA) level. The multivariate model revealed that both climatic and non-climatic factors were important for explaining spatio-temporal variations in incidence: mean relative humidity during November-June over the study region (posterior mean Incidence Rate Ratio (IRR) = 0.656, 95% Credible Interval (CI) 0.405-0.949) and occurrence of early rains in March in a HCCA (IRR = 0.353, 95% CI 0.239-0.502) were protective factors; a higher risk was associated with the percentage of neighbouring HCCAs having at least one MM A case during the same year (IRR = 2.365, 95% CI 2.078-2.695), the presence of a road crossing the HCCA (IRR = 1.743, 95% CI 1.173-2.474) and the occurrence of cases before 31 December in a HCCA (IRR = 6.801, 95% CI 4.004-10.910). At the study region level, higher annual incidence correlated with greater geographic spread and, to a lesser extent, with higher intensity of localized outbreaks.

CONCLUSIONS

Based on these findings, we hypothesize that spatio-temporal variability of MM A incidence between years and HCCAs result from variations in the intensity or duration of the dry season climatic effects on disease risk, and is further impacted by factors of spatial contacts, representing facilitated pathogen transmission. Additional unexplained factors may contribute to the observed incidence patterns and should be further investigated.

Dynamics of spatial clustering of schistosomiasis in the Yangtze River Valley at the end of and following the World Bank Loan Project

The 10-year (1992-2001) World Bank Loan Project (WBLP) contributed greatly to schistosomiasis control in China. However, the re-emergence of schistosomiasis in recent years challenged the long-term progress of the WBLP strategy. In order to gain insight in the long-term progress of the WBLP, the spatial pattern of the epidemic was investigated in the Yangtze River Valley between 1999-2001 and 2007-2008. Two spatial cluster methods were jointly used to identify spatial clusters of cases. The magnitude and number of clusters varied during 1999-2001. It was found that prevalence of schistosomiasis had been greatly reduced and maintained at a low level during 2007-2008, with little change. Besides, spatial clusters most frequently occurred within 16 counties in the Dongting Lake region and within 5 counties in the Poyang Lake region. These findings precisely pointed out the prior places for future public health planning and resource allocation of schistosomiasis.

Epidemiological changes in meningococcal meningitis in Niger from 2008 to 2011 and the impact of vaccination

Background

The epidemiology of bacterial meningitis in the African ‘meningitis belt’ changes periodically. In order to design an effective vaccination strategy, we have examined the epidemiological and microbiological patterns of bacterial meningitis, and especially that of meningococcal meningitis, in Niger during the period 2008–2011. During this period a mass vaccination campaign with the newly developed meningococcal A conjugate vaccine (MenAfriVac®) was undertaken.

Method

Cerebrospinal fluid samples were collected from health facilities throughout Niger and analysed by culture, seroagglutination and/or speciation polymerase chain reaction, followed by genogrouping PCR for Neisseria meningitidis infections. A sample of strains were analysed by multi-locus sequence typing.

Results

N. meningitidis serogroup A cases were prevalent in 2008 and 2009 [98.6% and 97.5% of all N. meningitidis cases respectively]. The prevalence of serogroup A declined in 2010 [26.4%], with the emergence of serogroup W Sequence Type (ST) 11 [72.2% of cases], and the serogroup A meningococcus finally disappeared in 2011. The geographical distribution of cases N. meningitidis serogroups A and W within Niger is described.

Conclusion

The substantial decline of serogroup A cases that has been observed from 2010 onwards in Niger seems to be due to several factors including a major polysaccharide A/C vaccination campaign in 2009, the introduction of MenAfriVac® in 10 districts at risk in December 2010, the natural dynamics of meningococcal infection and the persistence of serogroup A sequence-type 7 for about 10 years. The emergence of serogroup W strains suggests that there may be a need for serogroup W containing vaccines in Niger in the coming years.

Timely detection of bacterial meningitis epidemics at district level: a study in three countries of the African Meningitis Belt

BACKGROUND

Bacterial meningitis is a major public health problem in the African 'Meningitis Belt', where recurrent unpredictable epidemics occur. Despite the introduction in 2010 of the conjugate A vaccine, the reactive strategy remains important for responding to epidemics caused by other bacteria and in areas not yet vaccinated. Review of weekly numbers of suspected cases in Niger, Mali and Burkina Faso identified spatial disparities in the annual patterns of meningitis, which suggested a more local way of defining epidemics and initiating a timely vaccination campaign.

METHOD

We defined an epidemic district-year as an excess of cases compared to the incidence previously experienced in the given district. Groups of similar districts in terms of seasonal patterns were identified by cluster analysis. We investigated a cluster-specific criterion of early epidemic onset to anticipate epidemic district-years.

RESULTS

These were encouraging, as epidemic district-years were fairly efficiently captured, with an average time gained of 2.5 weeks over the current strategy.

CONCLUSION

This early-onset criterion could help ensure timely implementation of vaccination campaigns without the need to modify the implemented surveillance system. The next step is to extend this study to other countries of the Meningitis Belt, and to explain the differences in seasonal patterns in the different clusters.

Seasonality of meningitis in Africa and climate forcing: aerosols stand out

Bacterial meningitis is an ongoing threat for the population of the African Meningitis Belt, a region characterized by the highest incidence rates worldwide. The determinants of the disease dynamics are still poorly understood; nevertheless, it is often advocated that climate and mineral dust have a large impact. Over the last decade, several studies have investigated this relationship at a large scale. In this analysis, we scaled down to the district-level weekly scale (which is used for in-year response to emerging epidemics), and used wavelet and phase analysis methods to define and compare the time-varying periodicities of meningitis, climate and dust in Niger. We mostly focused on detecting time-lags between the signals that were consistent across districts. Results highlighted the special case of dust in comparison to wind, humidity or temperature: a strong similarity between districts is noticed in the evolution of the time-lags between the seasonal component of dust and meningitis. This result, together with the assumption of dust damaging the pharyngeal mucosa and easing bacterial invasion, reinforces our confidence in dust forcing on meningitis seasonality. Dust data should now be integrated in epidemiological and forecasting models to make them more realistic and usable in a public health perspective.

It's a long, long walk: accessibility to hospitals, maternity and integrated health centers in Niger

Background

Ease of access to health care is of great importance in any country but particularly in countries such as Niger where restricted access can put people at risk of mortality from diseases such as measles, meningitis, polio, pneumonia and malaria. This paper analyzes the physical access of populations to health facilities within Niger with an emphasis on the effect of seasonal conditions and the implications of these conditions in terms of availability of adequate health services, provision of drugs and vaccinations. The majority of the transport within Niger is pedestrian, thus the paper emphasizes access by those walking to facilities for care. Further analysis compared the change in accessibility for vehicular travel since public health workers do travel by vehicle when carrying out vaccination campaigns and related proactive health care activities.

Results

The majority of the roads in Niger are non-paved (90%). Six districts, mainly in the region of Tahoua lack medical facilities. Patient to health facility ratios were best in Agadez with 7000 people served per health facility. During the dry season 39% of the population was within 1-hours walk to a health center, with the percentage decreasing to 24% during the wet season. Further analyses revealed that vaccination rates were strongly correlated with distance. Children living in clusters within 1-hour of a health center had 1.88 times higher odds of complete vaccination by age 1-year compared to children living in clusters further from a health center (p < 0.05). Three key geographic areas were highlighted where access to health centers took greater than 4 h walk during the wet and dry season. Access for more than 730,000 people can be improved in these areas with the addition of 17 health facilities to the current total of 504 during the dry season (260,000 during the wet season).

Conclusions

This study highlights critical areas in Niger where health services/facilities are lacking. A second finding is that population served by health facilities will be severely overestimated if assessments are solely conducted during the dry season. Mapped outputs can be used for future decision making processes and analysis.