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Canine rabies, and thus human exposure to rabies, can be controlled through mass vaccination of the animal reservoir if dog owners are willing to cooperate. Inaccessible, ownerless dogs, however, reduce the vaccination coverage achieved in parenteral campaigns. This study aimed to estimate the vaccination coverage in dogs in three study zones of N'Djaména, Chad, after a pilot free parenteral mass vaccination campaign against rabies. We used a capture-mark-recapture approach for population estimates, with a Bayesian, Markov chain, Monte Carlo method to estimate the total number of owned dogs, and the ratio of ownerless to owned dogs to calculate vaccination coverage.When we took into account ownerless dogs, the vaccination coverage in the dog populations was 87% (95% confidence interval (CI), 84-89%) in study zone I, 71% (95% CI, 64-76%) in zone II, and 64% (95% CI, 58-71%) in zone III. The proportions of ownerless dogs to owned dogs were 1.1% (95% CI, 0-3.1%), 7.6% (95% CI, 0.7-16.5%), and 10.6%(95% CI, 1.6-19.1%) in the three study zones, respectively. Vaccination coverage in the three populations of owned dogs was 88% (95% CI, 840-92%) in zone I, 76% (95% CI, 71-81%) in zone II, and 70% (95% CI, 66-76%) in zone III. Participation of dog owners in the free campaign was high, and the number of inaccessible ownerless dogs was low. High levels of vaccination coverage could be achieved with parenteral mass vaccination. Regular parenteral vaccination campaigns to cover all of N'Djaména should be considered as an ethical way of preventing human rabies when post-exposure treatment is of limited availability and high in cost.

Abstract Background Mass vaccinations of domestic dogs have been shown to effectively control canine rabies and hence human exposure to rabies. Knowledge of dog population demography is essential for planning effective rabies vaccination programmes; however, such information is still rare for African domestic dog populations, particularly so in urban areas. This study describes the demographic structure and population dynamics of a domestic dog population in an urban sub-Saharan African setting. In July to November 2005, we conducted a full household-level census and a cross-sectional dog demography survey in four urban wards of Iringa Municipality, Tanzania. The achievable vaccination coverage was assessed by a two-stage vaccination campaign, and the proportion of feral dogs was estimated by a mark-recapture transect study. Results The estimated size of the domestic dog population in Iringa was six times larger than official town records assumed, however, the proportion of feral dogs was estimated to account for less than 1% of the whole population. An average of 13% of all households owned dogs which equalled a dog:human ratio of 1:14, or 0.31 dogs per household or 334 dogs km-2. Dog female:male ratio was 1:1.4. The average age of the population was 2.2 years, 52% of all individuals were less than one year old. But mortality within the first year was high (72%). Females became fertile at the age of 10 months and reportedly remained fertile up to the age of 11 years. The average number of litters whelped per fertile female per year was 0.6 with an average of 5.5 pups born per litter. The population growth was estimated at 10% y-1. Conclusions Such high birth and death rates result in a rapid replacement of anti-rabies immunised individuals with susceptible ones. This loss in herd immunity needs to be taken into account in the design of rabies control programmes. The very small proportion of truly feral dogs in the population implies that vaccination campaigns aimed at the owned dog population are sufficient to control rabies in urban Iringa, and the same may be valid in other, comparable urban settings.

Abstract Background In Côte d’Ivoire, an estimated 767,000 disability-adjusted life years are due to malaria, placing the country at position number 14 with regard to the global burden of malaria. Risk maps are important to guide control interventions, and hence, the aim of this study was to predict the geographical distribution of malaria infection risk in children aged Methods Using different data sources, a systematic review was carried out to compile and geo-reference survey data on Plasmodium spp. infection prevalence in Côte d’Ivoire, focusing on children aged Plasmodium spp. infection risk for entire Côte d’Ivoire, including uncertainty. Results Overall, 235 data points at 170 unique survey locations with malaria prevalence data for individuals aged Conclusion The malaria risk map at high spatial resolution gives an important overview of the geographical distribution of the disease in Côte d’Ivoire. It is a useful tool for the national malaria control programme and can be utilized for spatial targeting of control interventions and rational resource allocation.

Abstract Background Understanding the relationship between Plasmodium falciparum malaria transmission and health outcomes requires accurate estimates of exposure to infectious mosquitoes. However, measures of exposure such as mosquito density and entomological inoculation rate (EIR) are generally aggregated over large areas and time periods, biasing the outcome-exposure relationship. There are few studies examining the extent and drivers of local variation in malaria exposure in endemic areas. Methods We describe the spatio-temporal dynamics of malaria transmission intensity measured by mosquito density and EIR in the KEMRI/CDC health and demographic surveillance system using entomological data collected during 2002–2004. Geostatistical zero inflated binomial and negative binomial models were applied to obtain location specific (house) estimates of sporozoite rates and mosquito densities respectively. Model-based predictions were multiplied to estimate the spatial pattern of annual entomological inoculation rate, a measure of the number of infective bites a person receive per unit of time. The models included environmental and climatic predictors extracted from satellite data, harmonic seasonal trends and parameters describing space-time correlation. Results Anopheles gambiae s.l was the main vector species accounting for 86 % (n = 2309) of the total mosquitoes collected with the remainder being Anopheles funestus. Sixty eight percent (757/1110) of the surveyed houses had no mosquitoes. Distance to water bodies, vegetation and day temperature were strongly associated with mosquito density. Overall annual point estimates of EIR were 6.7, 9.3 and 9.6 infectious bites per annum for 2002, 2003 and 2004 respectively. Monthly mosquito density and EIR varied over the study period peaking in May during the wet season each year. The predicted and observed densities of mosquitoes and EIR showed a strong seasonal and spatial pattern over the study area. Conclusions Spatio-temporal maps of malaria transmission intensity obtained in this study are not only useful in understanding variability in malaria epidemiology over small areas but also provide a high resolution exposure surface that can be used to analyse the impact of transmission on malaria related and all-cause morbidity and mortality.

Abstract Background In Uganda, malaria and lymphatic filariasis (causative agent Wuchereria bancrofti) are transmitted by the same vector species of Anopheles mosquitoes, and thus are likely to share common environmental risk factors and overlap in geographical space. In a comprehensive nationwide survey in 2000-2003 the geographical distribution of W. bancrofti was assessed by screening school-aged children for circulating filarial antigens (CFA). Concurrently, blood smears were examined for malaria parasites. In this study, the resultant malariological data are analysed for the first time and the CFA data re-analysed in order to identify risk factors, produce age-stratified prevalence maps for each infection, and to define the geographical patterns of Plasmodium sp. and W. bancrofti co-endemicity. Methods Logistic regression models were fitted separately for Plasmodium sp. and W. bancrofti within a Bayesian framework. Models contained covariates representing individual-level demographic effects, school-level environmental effects and location-based random effects. Several models were fitted assuming different random effects to allow for spatial structuring and to capture potential non-linearity in the malaria- and filariasis-environment relation. Model-based risk predictions at unobserved locations were obtained via Bayesian predictive distributions for the best fitting models. Maps of predicted hyper-endemic malaria and filariasis were furthermore overlaid in order to define areas of co-endemicity. Results Plasmodium sp. parasitaemia was found to be highly endemic in most of Uganda, with an overall population adjusted parasitaemia risk of 47.2% in the highest risk age-sex group (boys 5-9 years). High W. bancrofti prevalence was predicted for a much more confined area in northern Uganda, with an overall population adjusted infection risk of 7.2% in the highest risk age-group (14-19 year olds). Observed overall prevalence of individual co-infection was 1.1%, and the two infections overlap geographically with an estimated number of 212,975 children aged 5 - 9 years living in hyper-co-endemic transmission areas. Conclusions The empirical map of malaria parasitaemia risk for Uganda presented in this paper is the first based on coherent, national survey data, and can serve as a baseline to guide and evaluate the continuous implementation of control activities. Furthermore, geographical areas of overlap with hyper-endemic W. bancrofti transmission have been identified to help provide a better informed platform for integrated control.

Abstract Background Reliable maps of the geographical distribution, number of infected individuals and burden estimates of schistosomiasis are essential tools to plan, monitor and evaluate control programmes. Large-scale disease mapping and prediction efforts rely on compiled historical survey data obtained from the peer-reviewed literature and unpublished reports. Schistosomiasis surveys usually focus on school-aged children, whereas some surveys include entire communities. However, data are often reported for non-standard age groups or entire study populations. Existing geostatistical models ignore either the age-dependence of the disease risk or omit surveys considered too heterogeneous. Methods We developed Bayesian geostatistical models and analysed existing schistosomiasis prevalence data by estimating alignment factors to relate surveys on individuals aged ≤ 20 years with surveys on individuals aged > 20 years and entire communities. Schistosomiasis prevalence data for 11 countries in the eastern African region were extracted from an open-access global database pertaining to neglected tropical diseases. We assumed that alignment factors were constant for the whole region or a specific country. Results Regional alignment factors indicated that the risk of a Schistosoma haematobium infection in individuals aged > 20 years and in entire communities is smaller than in individuals ≤ 20 years, 0.83 and 0.91, respectively. Country-specific alignment factors varied from 0.79 (Ethiopia) to 1.06 (Zambia) for community-based surveys. For S. mansoni, the regional alignment factor for entire communities was 0.96 with country-specific factors ranging from 0.84 (Burundi) to 1.13 (Uganda). Conclusions The proposed approach could be used to align inherent age-heterogeneity between school-based and community-based schistosomiasis surveys to render compiled data for risk mapping and prediction more accurate.

Abstract Background Infant mortality is an important indicator of population health in a country. It is associated with several health determinants, such as maternal health, access to high-quality health care, socioeconomic conditions, and public health policy and practices. Methods A spatial-temporal analysis was performed to assess changes in infant mortality patterns between 1992-2007 and to identify factors associated with infant mortality risk in the Agincourt sub-district, rural northeast South Africa. Period, sex, refugee status, maternal and fertility-related factors, household mortality experience, distance to nearest primary health care facility, and socio-economic status were examined as possible risk factors. All-cause and cause-specific mortality maps were developed to identify high risk areas within the study site. The analysis was carried out by fitting Bayesian hierarchical geostatistical negative binomial autoregressive models using Markov chain Monte Carlo simulation. Simulation-based Bayesian kriging was used to produce maps of all-cause and cause-specific mortality risk. Results Infant mortality increased significantly over the study period, largely due to the impact of the HIV epidemic. There was a high burden of neonatal mortality (especially perinatal) with several hot spots observed in close proximity to health facilities. Significant risk factors for all-cause infant mortality were mother's death in first year (most commonly due to HIV), death of previous sibling and increasing number of household deaths. Being born to a Mozambican mother posed a significant risk for infectious and parasitic deaths, particularly acute diarrhoea and malnutrition. Conclusions This study demonstrates the use of Bayesian geostatistical models in assessing risk factors and producing smooth maps of infant mortality risk in a health and socio-demographic surveillance system. Results showed marked geographical differences in mortality risk across a relatively small area. Prevention of vertical transmission of HIV and survival of mothers during the infants' first year in high prevalence villages needs to be urgently addressed, including expanded antenatal testing, prevention of mother-to-child transmission, and improved access to antiretroviral therapy. There is also need to assess and improve the capacity of district hospitals for emergency obstetric and newborn care. Persisting risk factors, including inadequate provision of clean water and sanitation, are yet to be fully addressed.

Abstract Background The Zambia Malaria Indicator Survey (ZMIS) of 2006 was the first nation-wide malaria survey, which combined parasitological data with other malaria indicators such as net use, indoor residual spraying and household related aspects. The survey was carried out by the Zambian Ministry of Health and partners with the objective of estimating the coverage of interventions and malaria related burden in children less than five years. In this study, the ZMIS data were analysed in order (i) to estimate an empirical high-resolution parasitological risk map in the country and (ii) to assess the relation between malaria interventions and parasitaemia risk after adjusting for environmental and socio-economic confounders. Methods The parasitological risk was predicted from Bayesian geostatistical and spatially independent models relating parasitaemia risk and environmental/climatic predictors of malaria. A number of models were fitted to capture the (potential) non-linearity in the malaria-environment relation and to identify the elapsing time between environmental effects and parasitaemia risk. These models included covariates (a) in categorical scales and (b) in penalized and basis splines terms. Different model validation methods were used to identify the best fitting model. Model-based risk predictions at unobserved locations were obtained via Bayesian predictive distributions for the best fitting model. Results Model validation indicated that linear environmental predictors were able to fit the data as well as or even better than more complex non-linear terms and that the data do not support spatial dependence. Overall the averaged population-adjusted parasitaemia risk was 20.0% in children less than five years with the highest risk predicted in the northern (38.3%) province. The odds of parasitaemia in children living in a household with at least one bed net decreases by 40% (CI: 12%, 61%) compared to those without bed nets. Conclusions The map of parasitaemia risk together with the prediction error and the population at risk give an important overview of the malaria situation in Zambia. These maps can assist to achieve better resource allocation, health management and to target additional interventions to reduce the burden of malaria in Zambia significantly. Repeated surveys will enable the evaluation of the effectiveness of on-going interventions.

Abstract Assessment of the relative impact of climate change on malaria dynamics is a complex problem. Climate is a well-known factor that plays a crucial role in driving malaria outbreaks in epidemic transmission areas. However, its influence in endemic environments with intensive malaria control interventions is not fully understood, mainly due to the scarcity of high-quality, long-term malaria data. The demographic surveillance systems in Africa offer unique platforms for quantifying the relative effects of weather variability on the burden of malaria. Here, using a process-based stochastic transmission model, we show that in the lowlands of malaria endemic western Kenya, variations in climatic factors played a key role in driving malaria incidence during 2008–2019, despite high bed net coverage and use among the population. The model captures some of the main mechanisms of human, parasite, and vector dynamics, and opens the possibility to forecast malaria in endemic regions, taking into account the interaction between future climatic conditions and intervention scenarios.

Abstract Background The objective of this study was to identify demographic, environmental and socioeconomic risk factors and spatial patterns of Plasmodium falciparum parasitaemia in a high endemicity area of Africa, and to specify how this information can facilitate improved malaria control at the district level. Methods A questionnaire was administered to about 4,000 schoolchildren in 55 schools in western Côte d'Ivoire to determine children's socioeconomic status and their habit of sleeping under bed nets. Environmental data were obtained from satellite images, digitized ground maps and a second questionnaire addressed to school directors. Finger prick blood samples were collected and P. falciparum parasitaemia determined under a microscope using standardized, quality-controlled methods. Bayesian variogram models were utilized for spatial risk modelling and mapping of P. falciparum parasitaemia at non-sampled locations, assuming stationary and non-stationary underlying spatial dependence. Results Two-thirds of the schoolchildren were infected with P. falciparum and the mean parasitaemia among infected children was 959 parasites/μl of blood. Age, socioeconomic status, not sleeping under a bed net, coverage rate with bed nets and environmental factors (e.g., normalized difference vegetation index, rainfall, land surface temperature and living in close proximity to standing water) were significantly associated with the risk of P. falciparum parasitaemia. After accounting for spatial correlation, age, bed net coverage, rainfall during the main malaria transmission season and distance to rivers remained significant covariates. Conclusion It is argued that a massive increase in bed net coverage, particularly in villages in close proximity to rivers, in concert with other control measures, is necessary to bring malaria endemicity down to intermediate or low levels.

Abstract Background Insecticide treated nets (ITN) have been proven to be an effective tool in reducing the burden of malaria. Few randomized clinical trials examined the spatial effect of ITNs on child mortality at a high coverage level, hence it is essential to better understand these effects in real-life situation with varying levels of coverage. We analyzed for the first time data from a large follow-up study in an area of high perennial malaria transmission in southern Tanzania to describe the spatial effects of bednets on all-cause child mortality. Methods The study was carried out between October 2001 and September 2003 in 25 villages in Kilombero Valley, southern Tanzania. Bayesian geostatistical models were fitted to assess the effect of different bednet density measures on child mortality adjusting for possible confounders. Results In the multivariate model addressing potential confounding, the only measure significantly associated with child mortality was the bed net density at household level; we failed to observe additional community effect benefit from bed net coverage in the community. Conclusion In this multiyear, 25 village assessment, despite substantial known inadequate insecticide-treatment for bed nets, the density of household bed net ownership was significantly associated with all cause child mortality reduction. The absence of community effect of bednets in our study area might be explained by (1) the small proportion of nets which are treated with insecticide, and (2) the relative homogeneity of coverage with nets in the area. To reduce malaria transmission for both users and non-users it is important to increase the ITNs and long-lasting nets coverage to at least the present untreated nets coverage.

Abstract Background Maps of the distribution of malaria vectors are useful tools for stratification of malaria risk and for selective vector control strategies. Although the distribution of members of the Anopheles gambiae complex is well documented in Africa, a continuous map of the spatial distribution of the chromosomal forms of An. gambiae s.s. is not yet available at country level to support control efforts. Methods Bayesian geostatistical methods were used to produce continuous maps of the spatial distribution of the chromosomal forms of An. gambiae s.s. (Mopti, Bamako, Savanna and their hybrids/recombinants) based on their relative frequencies in relation to climatic and environmental factors in Mali. Results The maps clearly show that each chromosomal form favours a particular defined eco-climatic zone. The Mopti form prefers the dryer northern Savanna and Sahel and the flooded/irrigated areas of the inner delta of the Niger River. The Savanna form favours the Sudan savanna areas, particularly the South and South-Eastern parts of the country (Kayes and Sikasso regions). The Bamako form has a strong preference for specific environmental conditions and it is confined to the Sudan savanna areas around urban Bamako and the Western part of Sikasso region. The hybrids/recombinants favour the Western part of the country (Kayes region) bordering the Republic of Guinea Conakry. Conclusion The maps provide valuable information for selective vector control in Mali (insecticide resistance management) and may serve as a decision support tool for the basis for future malaria control strategies including genetically manipulated mosquitoes.

Abstract Background There is a renewed political will and financial support to eradicate malaria. Spatially-explicit risk profiling will play an important role in this endeavour. Patterns of Plasmodium falciparum infection prevalence were examined among schoolchildren in a highly malaria-endemic area. Methods A questionnaire was administered and finger prick blood samples collected from 3,962 children, aged six to 16 years, attending 55 schools in a rural part of western Côte d'Ivoire. Information was gathered from the questionnaire on children's socioeconomic status and the use of bed nets for the prevention of malaria. Blood samples were processed with standardized, quality-controlled methods for diagnosis of Plasmodium spp. infections. Environmental data were obtained from satellite images and digitized maps. Bayesian variogram models for spatially-explicit risk modelling of P. falciparum infection prevalence were employed, assuming for stationary and non-stationary spatial processes. Findings The overall prevalence of P. falciparum infection was 64.9%, ranging between 34.0% and 91.9% at the unit of the school. Risk factors for a P. falciparum infection included age, socioeconomic status, not sleeping under a bed net, distance to health care facilities and a number of environmental features (i.e. normalized difference vegetation index, rainfall and distance to rivers). After taking into account spatial correlation only age remained significant. Non-stationary models performed better than stationary models. Conclusion Spatial risk profiling of P. falciparum prevalence data provides a useful tool for targeting malaria control intervention, and hence will play a role in the quest of local elimination and ultimate eradication of the disease.

Abstract Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed.

Abstract Background Rainfall data have potential use for malaria prediction. However, the relationship between rainfall and the number of malaria cases is indirect and complex. Methods The statistical relationships between monthly malaria case count data series and monthly mean rainfall series (extracted from interpolated station data) over the period 1972 – 2005 in districts in Sri Lanka was explored in four analyses: cross-correlation; cross-correlation with pre-whitening; inter-annual; and seasonal inter-annual regression. Results For most districts, strong positive correlations were found for malaria time series lagging zero to three months behind rainfall, and negative correlations were found for malaria time series lagging four to nine months behind rainfall. However, analysis with pre-whitening showed that most of these correlations were spurious. Only for a few districts, weak positive (at lags zero and one) or weak negative (at lags two to six) correlations were found in pre-whitened series. Inter-annual analysis showed strong negative correlations between malaria and rainfall for a group of districts in the centre-west of the country. Seasonal inter-annual analysis showed that the effect of rainfall on malaria varied according to the season and geography. Conclusion Seasonally varying effects of rainfall on malaria case counts may explain weak overall cross-correlations found in pre-whitened series, and should be taken into account in malaria predictive models making use of rainfall as a covariate.

Abstract Background An estimated 40 % of the population in Benin lives in urban areas. The purpose of the study was to estimate malaria endemicity and the fraction of malaria-attributable fevers in health facilities in Cotonou. Methods A health care system evaluation and a series of school parasitaemia surveys and health facility-based surveys were carried out during the dry season in of 2003, applying standard Rapid Urban Malaria Appraisal (RUMA) methodology. This study was part of a multi-site assessment supported by the Roll Back Malaria Partnership. Results The field work was carried out in February-March 2003. In 2002 and out of 289,342 consultations in the public health facilities of Cotonou there were 100,257 reported simple malaria cases (34.6%) and 12,195 complicated malaria cases (4.2%). In the school parasitaemia surveys, a malaria infection was found in 5.2 % of all samples. The prevalence rates of parasitaemia in the centre, intermediate and periphery zones were 2.6%, 9.0% and 2.5%, respectively. In the health facility surveys the malaria infection rates in presenting fever cases were 0% (under one year old), 6.8% (one to five years old), 0% (> five to 15 years old) and 0.9% (over 15 years old), while these rates in the control group were 1.4%, 2.8%, 1.3% and 2.0%. The malaria-attributable fractions among presenting fever cases were 0.04 in the one to five years old and zero in the three other age groups. Hence, malaria played only a small role in fever episodes at the end of the dry season. In total, 69.2% of patients used a mosquito net the night before the survey and 35.1% used an insecticide-treated net, which was shown to be protective for an infection (OR = 0.23, 95% CI 0.07–0.78). Travelling to a rural area (5.8% of all respondents) did not increase the infection risk. Conclusion The homogenously low malaria prevalence might be associated with urban transformation and/or a high bednet usage. Over-diagnosis of malaria and over-treatment with antimalarials was found to be a serious problem.

Abstract Background On the fringes of endemic zones climate is a major determinant of inter-annual variation in malaria incidence. Quantitative description of the space-time effect of this association has practical implications for the development of operational malaria early warning system (MEWS) and malaria control. We used Bayesian negative binomial models for spatio-temporal analysis of the relationship between annual malaria incidence and selected climatic covariates at a district level in Zimbabwe from 1988–1999. Results Considerable inter-annual variations were observed in the timing and intensity of malaria incidence. Annual mean values of average temperature, rainfall and vapour pressure were strong positive predictors of increased annual incidence whereas maximum and minimum temperature had the opposite effects. Our modelling approach adjusted for unmeasured space-time varying risk factors and showed that while year to year variation in malaria incidence is driven mainly by climate, the resultant spatial risk pattern may to large extent be influenced by other risk factors except during high and low risk years following the occurrence of extremely wet and dry conditions, respectively. Conclusion Our model revealed a spatially varying risk pattern that is not attributable only to climate. We postulate that only years characterized by extreme climatic conditions may be important for developing climate based MEWS and for delineating areas prone to climate driven epidemics. However, the predictive value of climatic risk factors identified in this study still needs to be evaluated.

Abstract Background Currently, there is a significant lack of knowledge concerning urban malaria patterns in general and in Abidjan in particular. The prevalence of malaria, its distribution in the city and the fractions of fevers attributable to malaria in the health facilities have not been previously investigated. Methods A health facility-based survey and health care system evaluation was carried out in a peripheral municipality of Abidjan (Yopougon) during the rainy season of 2002, applying a standardized Rapid Urban Malaria Appraisal (RUMA) methodology. Results According to national statistics, approximately 240,000 malaria cases (both clinical cases and laboratory confirmed cases) were reported by health facilities in the whole of Abidjan in 2001. They accounted for 40% of all consultations. In the health facilities of the Yopougon municipality, the malaria infection rates in fever cases for different age groups were 22.1% (under one year-olds), 42.8% (one to five years-olds), 42.0% (> five to 15 years-olds) and 26.8% (over 15 years-olds), while those in the control group were 13.0%. 26.7%, 21.8% and 14.6%, respectively. The fractions of malaria-attributable fever were 0.12, 0.22, 0.27 and 0.13 in the same age groups. Parasitaemia was homogenously detected in different areas of Yopougon. Among all children, 10.1% used a mosquito net (treated or not) the night before the survey and this was protective (OR = 0.52, 95% CI 0.29–0.97). Travel to rural areas within the last three months was frequent (31% of all respondents) and associated with a malaria infection (OR = 1.75, 95% CI 1.25–2.45). Conclusion Rapid urbanization has changed malaria epidemiology in Abidjan and endemicity was found to be moderate in Yopougon. Routine health statistics are not fully reliable to assess the burden of disease, and the low level of the fractions of malaria-attributable fevers indicated substantial over-treatment of malaria.

Abstract Background Rapid urbanization in sub-Saharan Africa has a major impact on malaria epidemiology. While much is known about malaria in rural areas in Burkina Faso, the urban situation is less well understood. Methods An assessment of urban malaria was carried out in Ouagadougou in November -December, 2002 during which a rapid urban malaria appraisal (RUMA) was applied. Results The school parasitaemia prevalence was relatively high (48.3%) at the cold and dry season 2002. Routine malaria statistics indicated that seasonality of malaria transmission was marked. In the health facilities, the number of clinical cases diminished quickly at the start of the cold and dry season and the prevalence of parasitaemia detected in febrile and non-febrile cases was 21.1% and 22.0%, respectively. The health facilities were likely to overestimate the malaria incidence and the age-specific fractions of malaria-attributable fevers were low (0–0.13). Peak prevalence tended to occur in older children (aged 6–15 years). Mapping of Anopheles sp. breeding sites indicated a gradient of endemicity between the urban centre and the periphery of Ouagadougou. A remarkable link was found between urban agriculture activities, seasonal availability of water supply and the occurrence of malaria infections in this semi-arid area. The study also demonstrated that the usage of insecticide-treated nets and the education level of family caretakers played a key role in reducing malaria infection rates. Conclusion These findings show that determining local endemicity and the rate of clinical malaria cases are urgently required in order to target control activities and avoid over-treatment with antimalarials. The case management needs to be tailored to the level of the prevailing endemicity.

Abstract Background The rapid urban malaria appraisal (RUMA) methodology aims to provide a cost-effective tool to conduct rapid assessments of the malaria situation in urban sub-Saharan Africa and to improve the understanding of urban malaria epidemiology. Methods This work was done in Yopougon municipality (Abidjan), Cotonou, Dar es Salaam and Ouagadougou. The study design consists of six components: 1) a literature review, 2) the collection of available health statistics, 3) a risk mapping, 4) school parasitaemia surveys, 5) health facility-based surveys and 6) a brief description of the health care system. These formed the basis of a multi-country evaluation of RUMA's feasibility, consistency and usefulness. Results A substantial amount of literature (including unpublished theses and statistics) was found at each site, providing a good overview of the malaria situation. School and health facility-based surveys provided an overview of local endemicity and the overall malaria burden in different city areas. This helped to identify important problems for in-depth assessment, especially the extent to which malaria is over-diagnosed in health facilities. Mapping health facilities and breeding sites allowed the visualization of the complex interplay between population characteristics, health services and malaria risk. However, the latter task was very time-consuming and required special expertise. RUMA is inexpensive, costing around 8,500–13,000 USD for a six to ten-week period. Conclusion RUMA was successfully implemented in four urban areas with different endemicity and proved to be a cost-effective first approach to study the features of urban malaria and provide an evidence basis for planning control measures.

BackgroundIn Bangladesh, preventive chemotherapy targeting soil-transmitted helminth (STH) infections in school-age children has been implemented since 2008. To evaluate the success of this strategy, surveys were conducted between 2017 and 2020 in 10 out of 64 districts. We estimate the geographic distribution of STH infections by species at high spatial resolution, identify risk factors, and estimate treatment needs at different population subgroups.MethodologyBayesian geostatistical models were fitted to prevalence data of each STH species. Climatic, environmental, and socioeconomic predictors were extracted from satellite images, open-access, model-based databases, and demographic household surveys, and used to predict the prevalence of infection over a gridded surface at 1 x 1 km spatial resolution across the country, via Bayesian kriging. These estimates were combined with gridded population data to estimate the number of required treatments for different risk groups.Principal findingsThe population-adjusted prevalence of Ascaris lumbricoides, Trichuris trichiura, and hookworm across all ages is estimated at 9.9% (95% Bayesian credible interval: 8.0-13.0%), 4.3% (3.0-7.3%), and 0.6% (0.4-0.9%), respectively. There were 24 out of 64 districts with an estimated population-adjusted STH infection prevalence above 20%. The proportion of households with improved sanitation showed a statistically important, protective association for both, A. lumbricoides and T. trichiura prevalence. Precipitation in the driest month of the year was negatively associated with A. lumbricoides prevalence. High organic carbon concentration in the soil's fine earth fraction was related to a high hookworm prevalence. Furthermore, we estimated that 30.5 (27.2; 36.0) million dosages of anthelmintic treatments for school-age children were required per year in Bangladesh.Conclusions/significanceFor each of the STH species, the prevalence was reduced by at least 80% since treatment was scaled up more than a decade ago. The current number of deworming dosages could be reduced by up to 61% if the treatment strategy was adapted to the local prevalence.

Background: Despite considerable progress made over the past 20 years in reducing the global burden of malaria, the disease remains a major public health problem and there is concern that climate change might expand suitable areas for transmission. This study investigated the relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya. Methods: Bayesian negative binomial models were fitted to monthly malaria incidence data, extracted from records of patients with febrile illnesses visiting the Lwak Mission Hospital between 2008 and 2019. Data pertaining to bed net use and socio-economic status (SES) were obtained from household surveys. Climatic proxy variables obtained from remote sensing were included as covariates in the models. Bayesian variable selection was used to determine the elapsing time between climate suitability and malaria incidence. Results: Malaria incidence increased by 50% from 2008 to 2010, then declined by 73% until 2015. There was a resurgence of cases after 2016, despite high bed net use. Increase in daytime land surface temperature was associated with a decline in malaria incidence (incidence rate ratio [IRR] = 0.70, 95% Bayesian credible interval [BCI]: 0.59–0.82), while rainfall was associated with increased incidence (IRR = 1.27, 95% BCI: 1.10–1.44). Bed net use was associated with a decline in malaria incidence in children aged 6–59 months (IRR = 0.78, 95% BCI: 0.70–0.87) but not in older age groups, whereas SES was not associated with malaria incidence in this population. Conclusions: Variability in climatic factors showed a stronger effect on malaria incidence than bed net use. Bed net use was, however, associated with a reduction in malaria incidence, especially among children aged 6–59 months after adjusting for climate effects. To sustain the downward trend in malaria incidence, this study recommends continued distribution and use of bed nets and consideration of climate-based malaria early warning systems when planning for future control interventions.

Abstract Background Most older adults prefer to continue living at home despite increasing care needs and demand for services. To aid in maintaining independence, integrated care models for community-dwelling older people are promoted as the most cost-effective approach. The implementation of such care models is challenging and often the end-users are not involved or their needs are not considered. We conducted a population survey in order to understand the needs and preferences of home-dwelling older adults living in Canton Basel-Landschaft, Switzerland. The aims of this paper are to chronicle the development of the INSPIRE Population Survey, outline its variables and measurements, describe the marketing strategy utilized for survey dissemination and report on the response rate and respondent characteristics. Methods The INSPIRE Population Survey, conducted between March and August 2019, is a cross-sectional survey of older adults aged 75 and older living at home in Canton Basel-Landschaft. The questionnaire was developed by expert input and stakeholder involvement. Its readability and acceptability were pilot-tested with older people. To ensure the likelihood of a high and representative response rate, a meticulous step-by-step marketing strategy was developed prior to the dissemination of the questionnaire. Results The overall response rate was 30.7% (n = 8,846), with variations between 20.6 and 34.5% across the different care regions in the canton. A generally higher response rate was found in the care regions with a higher density and which bordered the urban city of Basel. We received support from local stakeholders, policy makers and media through using a broad combination of marketing channels and targeting our community partners who have a strong relationship with our target audience. Conclusions Although recruiting older adults in research is challenging, our study shows that a high response rate can be achieved by developing the survey through expert input and by involving all important stakeholders, including older adults, throughout the entire process.

Abstract Background The Service Availability and Readiness Assessment surveys generate data on the readiness of health facility services. We constructed a readiness index related to malaria services and determined the association between health facility malaria readiness and malaria mortality in children under the age of 5 years in Burkina Faso. Methods Data on inpatients visits and malaria-related deaths in under 5-year-old children were extracted from the national Health Management Information System in Burkina Faso. Bayesian geostatistical models with variable selection were fitted to malaria mortality data. The most important facility readiness indicators related to general and malaria-specific services were determined. Multiple correspondence analysis (MCA) was employed to construct a composite facility readiness score based on multiple factorial axes. The analysis was carried out separately for 112 medical centres and 546 peripheral health centres. Results Malaria mortality rate in medical centres was 4.8 times higher than that of peripheral health centres (3.5% vs. 0.7%, p

BackgroundWorld Health Organization (WHO) guidelines for measuring global progress in schistosomiasis control classify individuals with Schistosoma spp. infections based on the concentration of excreted eggs. We assessed the associations between WHO infection intensity categories and morbidity prevalence for selected S. haematobium and S. mansoni morbidities in school-age children.MethodologyA total of 22,488 children aged 6-15 years from monitoring and evaluation cohorts in Burkina Faso, Mali, Niger, Uganda, Tanzania, and Zambia from 2003-2008 were analyzed using Bayesian logistic regression. Models were utilized to evaluate associations between intensity categories and the prevalence of any urinary bladder lesion, any upper urinary tract lesion, microhematuria, and pain while urinating (for S. haematobium) and irregular hepatic ultrasound image pattern (C-F), enlarged portal vein, laboratory-confirmed diarrhea, and self-reported diarrhea (for S. mansoni) across participants with infection and morbidity data.Principal findingsS. haematobium infection intensity categories possessed consistent morbidity prevalence across surveys for multiple morbidities and participants with light infections had elevated morbidity levels, compared to negative participants. Conversely, S. mansoni infection intensity categories lacked association with prevalence of the morbidity measures assessed.Conclusions/significanceCurrent status infection intensity categories for S. haematobium were associated with morbidity levels in school-age children, suggesting urogenital schistosomiasis morbidity can be predicted by an individual's intensity category. Conversely, S. mansoni infection intensity categories were not consistently indicative of childhood morbidity at baseline or during the first two years of a preventive chemotherapy control program.

BackgroundThe prevalence of Schistosoma mansoni infection is usually assessed by the Kato-Katz diagnostic technique. However, Kato-Katz thick smears have low sensitivity, especially for light infections. Egg count models fitted on individual level data can adjust for the infection intensity-dependent sensitivity and estimate the 'true' prevalence in a population. However, application of these models is complex and there is a need for adjustments that can be done without modeling expertise. This study provides estimates of the 'true' S. mansoni prevalence from population summary measures of observed prevalence and infection intensity using extensive simulations parametrized with data from different settings in sub-Saharan Africa.MethodologyAn individual-level egg count model was applied to Kato-Katz data to determine the S. mansoni infection intensity-dependent sensitivity for various sampling schemes. Observations in populations with varying forces of transmission were simulated, using standard assumptions about the distribution of worms and their mating behavior. Summary measures such as the geometric mean infection, arithmetic mean infection, and the observed prevalence of the simulations were calculated, and parametric statistical models fitted to the summary measures for each sampling scheme. For validation, the simulation-based estimates are compared with an observational dataset not used to inform the simulation.Principal findingsOverall, the sensitivity of Kato-Katz in a population varies according to the mean infection intensity. Using a parametric model, which takes into account different sampling schemes varying from single Kato-Katz to triplicate slides over three days, both geometric and arithmetic mean infection intensities improve estimation of sensitivity. The relation between observed and 'true' prevalence is remarkably linear and triplicate slides per day on three consecutive days ensure close to perfect sensitivity.Conclusions/significanceEstimation of 'true' S. mansoni prevalence is improved when taking into account geometric or arithmetic mean infection intensity in a population. We supply parametric functions and corresponding estimates of their parameters to calculate the 'true' prevalence for sampling schemes up to 3 days with triplicate Kato-Katz thick smears per day that allow estimation of the 'true' prevalence.

BackgroundSchistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and belongs to the neglected tropical diseases. The disease has been reported in 78 countries, with around 290.8 million people in need of treatment in 2018. Schistosomiasis is predominantly considered a rural disease with a subsequent focus of research and control activities in rural settings. Over the past decades, occurrence and even expansion of schistosomiasis foci in peri-urban and urban settings have increasingly been observed. Rural-urban migration in low- and middle-income countries and subsequent rapid and unplanned urbanization are thought to explain these observations. Fifty-five percent (55%) of the world population is already estimated to live in urban areas, with a projected increase to 68% by 2050. In light of rapid urbanization and the efforts to control morbidity and ultimately achieve elimination of schistosomiasis, it is important to deepen our understanding of the occurrence, prevalence, and transmission of schistosomiasis in urban and peri-urban settings. A systematic literature review looking at urban and peri-urban schistosomiasis was therefore carried out as a first step to address the research and mapping gap.MethodologyFollowing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic computer-aided literature review was carried out using PubMed, ScienceDirect, and the World Health Organization Database in November 2019, which was updated in March 2020. Only papers for which at least the abstract was available in English were used. Relevant publications were screened, duplicates were removed, guidelines for eligibility were applied, and eligible studies were reviewed. Studies looking at human Schistosoma infections, prevalence, and intensity of infection in urban and peri-urban settings were included as well as those focusing on the intermediate host snails.Principal findingsA total of 248 publications met the inclusion criteria. The selected studies confirm that schistosomiasis is prevalent in peri-urban and urban areas in the countries assessed. Earlier studies report higher prevalence levels in urban settings compared to data extracted from more recent publications, yet the challenge of migration, rapid uncontrolled urbanization, and resulting poor living conditions highlight the potential for continuous or even newly established transmission to take place.ConclusionsThe review indicates that schistosomiasis has long existed in urban and peri-urban areas and remains a public health problem. There is, however, a challenge of comparability of settings due to the lack of a clear definition of what constitutes urban and peri-urban. There is a pressing need for improved monitoring of schistosomiasis in urban communities and consideration of treatment strategies.

BackgroundTreatment needs for Schistosoma haematobium are commonly evaluated using urine filtration with detection of parasite eggs under a microscope. A common symptom of S. haematobium is hematuria, the passing of blood in urine. Hence, the use of hematuria-based diagnostic techniques as a proxy for the assessment of treatment needs has been considered. This study evaluates data from a national survey in Zimbabwe, where three hematuria-based diagnostic techniques, that is microhematuria, macrohematuria, and an anamnestic questionnaire pertaining to self-reported blood in urine, have been included in addition to urine filtration in 280 schools across 70 districts.MethodologyWe developed an egg count model, which evaluates the infection intensity-dependent sensitivity and the specificity of each diagnostic technique without relying on a 'gold' standard. Subsequently, we determined prevalence thresholds for each diagnostic technique, equivalent to a 10% urine filtration-based prevalence and compared classification of districts according to treatment strategy based on the different diagnostic methods.Principal findingsA 10% urine filtration prevalence threshold corresponded to a 17.9% and 13.3% prevalence based on questionnaire and microhematuria, respectively. Both the questionnaire and the microhematuria showed a sensitivity and specificity of more than 85% for estimating treatment needs at the above thresholds. For diagnosis at individual level, the questionnaire showed the highest sensitivity (70.0%) followed by urine filtration (53.8%) and microhematuria (52.2%).Conclusions/significanceThe high sensitivity and specificity of a simple questionnaire to estimate treatment needs of S. haematobium suggests that it can be used as a rapid, low-cost method to estimate district prevalence. Our modeling approach can be expanded to include setting-dependent specificity of the technique and should be assessed in relation to other diagnostic methods due to potential cross-reaction with other diseases.

BackgroundStrongyloides stercoralis is a neglected soil-transmitted helminth that occurs worldwide, though it is particularly endemic in tropical and subtropical areas. It can cause long-lasting and potentially fatal infections due to its ability to replicate within its host. S. stercoralis causes gastrointestinal and dermatological morbidity. The objective of this study was to assess the S. stercoralis infection risk and, using geostatistical models, to predict its geographical distribution in Cambodia.Methodology / principal findingsA nation-wide, community-based parasitological survey was conducted among the Cambodian population, aged 6 years and older. S. stercoralis was diagnosed using a serological diagnostic test that detects IgG antibodies in urine. Data on demography, hygiene and knowledge about helminth infection were collected. S. stercoralis prevalence among 7,246 participants with a complete data record was 30.5%, ranging from 10.9% to 48.2% across provinces. The parasite was ubiquitous in Cambodia; only five south-eastern provinces had prevalence rates below 20%. Infection risk increased with age for both men and women, although girls under the age of 13 and women aged 50 years and over had lower odds of infection than their male counterparts. Open defecation was associated with higher odds of infection, while having some knowledge of the health problems caused by worms was a protective factor. Infection risk was positively associated with nighttime maximum temperature, minimum rainfall, and distance to water; it was negatively associated with land occupied by rice fields.Conclusions / significanceS. stercoralis infection is rampant in Cambodia. Control programs delivering ivermectin are needed to manage the parasite. However, the high cost of this drug in Cambodia currently precludes the implementation of control initiatives. Donations, subsidies or affordable generics are needed so that S. stercoralis, which infects almost a third of the Cambodian population, can be addressed through an adequate control program.

BACKGROUND:Over the past 15 years, scaling up of cost effective interventions resulted in a remarkable decline of under-five mortality rates (U5MR) in sub-Saharan Africa. However, the reduction shows considerable heterogeneity. We estimated the association of child, maternal, and household interventions with U5MR in Burkina Faso at national and subnational levels and identified the regions with least effective interventions. METHODS:Data on health-related interventions and U5MR were extracted from the Burkina Faso Demographic and Health Survey (DHS) 2010. Bayesian geostatistical proportional hazards models with a Weibull baseline hazard were fitted on the mortality outcome. Spatially varying coefficients were considered to assess the geographical variation in the association of the health interventions with U5MR. The analyses were adjusted for child, maternal, and household characteristics, as well as climatic and environmental factors. FINDINGS:The average U5MR was as high as 128 per 1000 ranging from 81 (region of Centre-Est) to 223 (region of Sahel). At national level, DPT3 immunization and baby post-natal check within 24 hours after birth had the most important association with U5MR (hazard rates ratio (HRR) = 0.89, 95% Bayesian credible interval (BCI): 0.86-0.98 and HRR = 0.89, 95% BCI: 0.86-0.92, respectively). At sub-national level, the most effective interventions are the skilled birth attendance, and improved drinking water, followed by baby post-natal check within 24 hours after birth, vitamin A supplementation, antenatal care visit and all-antigens immunization (including BCG, Polio3, DPT3, and measles immunization). Centre-Est, Sahel, and Sud-Ouest were the regions with the highest number of effective interventions. There was no intervention that had a statistically important association with child survival in the region of Hauts Bassins. INTERPRETATION:The geographical variation in the magnitude and statistical importance of the association between health interventions and U5MR raises the need to deliver and reinforce health interventions at a more granular level. Priority interventions are DPT3 immunization, skilled birth attendance, baby post-natal visits in the regions of Sud-Ouest, Sahel, and Hauts Bassins, respectively. Our methodology could be applied to other national surveys, as it allows an incisive, data-driven and specific decision-making approach to optimize the allocation of health interventions at subnational level.

Abstract Background Quantification of malaria heterogeneity is very challenging, partly because of the underlying characteristics of mosquitoes and also because malaria is an environmentally driven disease. Furthermore, in order to assess the spatial and seasonal variability in malaria transmission, vector data need to be collected repeatedly over time (at fixed geographical locations). Measurements collected at locations close to each other and over time tend to be correlated because of common exposures such as environmental or climatic conditions. Non- spatial statistical methods, when applied to analyze such data, may lead to biased estimates. We developed rigorous methods for analyzing sparse and spatially correlated data. We applied Bayesian variable selection to identify the most important predictors as well as the elapsing time between climate suitability and changes in entomological indices. Methods Bayesian geostatistical zero-inflated binomial and negative binomial models including harmonic seasonal terms, temporal trends and climatic remotely sensed proxies were applied to assess spatio-temporal variation of sporozoite rate and mosquito density in the study area. Bayesian variable selection was employed to determine the most important climatic predictors and elapsing (lag) time between climatic suitability and malaria transmission. Bayesian kriging was used to predict mosquito density and sporozoite rate at unsampled locations. These estimates were converted to covariate and season-adjusted maps of entomological inoculation rates. Models were fitted using Markov chain Monte Carlo simulation. Results The results show that Anophele. gambiae is the most predominant vector (79.29%) and is more rain-dependant than its sibling Anophele. funestus (20.71%). Variable selection suggests that the two species react differently to different climatic conditions. Prediction maps of entomological inoculation rate (EIR) depict a strong spatial and temporal heterogeneity in malaria transmission risk despite the relatively small geographical extend of the study area. Conclusion Malaria transmission is very heterogeneous over the study area. The EIR maps clearly depict a strong spatial and temporal heterogeneity despite the relatively small geographical extend of the study area. Model based estimates of transmission can be used to identify high transmission areas in order to prioritise interventions and support research in malaria epidemiology.