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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.

The effect of malaria exposure on mortality using health facility incidence data as a measure of transmission has not been well investigated. Health and demographic surveillance systems (HDSS) routinely capture data on mortality, interventions and other household related indicators, offering a unique platform for estimating and monitoring the incidence-mortality relationship in space and time.Mortality data from the HDSS located in Western Kenya collected from 2007 to 2012 and linked to health facility incidence data were analysed using Bayesian spatio-temporal survival models to investigate the relation between mortality (all-cause/malaria-specific) and malaria incidence across all age groups. The analysis adjusted for insecticide-treated net (ITN) ownership, socio-economic status (SES), distance to health facilities and altitude. The estimates obtained were used to quantify excess mortality due to malaria exposure.Our models identified a strong positive relationship between slide positivity rate (SPR) and all-cause mortality in young children 1-4 years (HR = 4.29; 95% CI: 2.78-13.29) and all ages combined (HR = 1.55; 1.04-2.80). SPR had a strong positive association with malaria-specific mortality in young children (HR = 9.48; 5.11-37.94), however, in older children (5-14 years), it was associated with a reduction in malaria specific mortality (HR = 0.02; 0.003-0.33).SPR as a measure of transmission captures well the association between malaria transmission intensity and all-cause/malaria mortality. This offers a quick and efficient way to monitor malaria burden. Excess mortality estimates indicate that small changes in malaria incidence substantially reduce overall and malaria specific mortality.

BACKGROUND:Malaria burden in Uganda has declined disproportionately among regions despite overall high intervention coverage across all regions. The Uganda Malaria Indicator Survey (MIS) 2014-15 was the second nationally representative survey conducted to provide estimates of malaria prevalence among children less than 5 years, and to track the progress of control interventions in the country. In this present study, 2014-15 MIS data were analysed to assess intervention effects on malaria prevalence in Uganda among children less than 5 years, assess intervention effects at regional level, and estimate geographical distribution of malaria prevalence in the country. METHODS:Bayesian geostatistical models with spatially varying coefficients were used to determine the effect of interventions on malaria prevalence at national and regional levels. Spike-and-slab variable selection was used to identify the most important predictors and forms. Bayesian kriging was used to predict malaria prevalence at unsampled locations. RESULTS:Indoor Residual Spraying (IRS) and Insecticide Treated Nets (ITN) ownership had a significant but varying protective effect on malaria prevalence. However, no effect was observed for Artemisinin Combination-based Therapies (ACTs). Environmental factors, namely, land cover, rainfall, day and night land surface temperature, and area type were significantly associated with malaria prevalence. Malaria prevalence was higher in rural areas, increased with the child's age, and decreased with higher household socioeconomic status and higher level of mother's education. The highest prevalence of malaria in children less than 5 years was predicted for regions of East Central, North East and West Nile, whereas the lowest was predicted in Kampala and South Western regions, and in the mountainous areas in Mid-Western and Mid-Eastern regions. CONCLUSIONS:IRS and ITN ownership are important interventions against malaria prevalence in children less than 5 years in Uganda. The varying effects of the interventions calls for selective implementation of control tools suitable to regional ecological settings. To further reduce malaria burden and sustain malaria control in Uganda, current tools should be supplemented by health system strengthening, and socio-economic development.

INTRODUCTION: With the renewed drive towards malaria elimination, there is a need for improved surveillance tools. While time series analysis is an important tool for surveillance, prediction and for measuring interventions' impact, approximations by commonly used Gaussian methods are prone to inaccuracies when case counts are low. Therefore, statistical methods appropriate for count data are required, especially during "consolidation" and "pre-elimination" phases. METHODS: Generalized autoregressive moving average (GARMA) models were extended to generalized seasonal autoregressive integrated moving average (GSARIMA) models for parsimonious observation-driven modelling of non Gaussian, non stationary and/or seasonal time series of count data. The models were applied to monthly malaria case time series in a district in Sri Lanka, where malaria has decreased dramatically in recent years. RESULTS: The malaria series showed long-term changes in the mean, unstable variance and seasonality. After fitting negative-binomial Bayesian models, both a GSARIMA and a GARIMA deterministic seasonality model were selected based on different criteria. Posterior predictive distributions indicated that negative-binomial models provided better predictions than Gaussian models, especially when counts were low. The G(S)ARIMA models were able to capture the autocorrelation in the series. CONCLUSIONS: G(S)ARIMA models may be particularly useful in the drive towards malaria elimination, since episode count series are often seasonal and non-stationary, especially when control is increased. Although building and fitting GSARIMA models is laborious, they may provide more realistic prediction distributions than do Gaussian methods and may be more suitable when counts are low.

The Research Center for Human Development in Dakar (CRDH) with the technical assistance of ICF Macro and the National Malaria Control Programme (NMCP) conducted in 2008/2009 the Senegal Malaria Indicator Survey (SMIS), the first nationally representative household survey collecting parasitological data and malaria-related indicators. In this paper, we present spatially explicit parasitaemia risk estimates and number of infected children below 5 years. Geostatistical Zero-Inflated Binomial models (ZIB) were developed to take into account the large number of zero-prevalence survey locations (70%) in the data. Bayesian variable selection methods were incorporated within a geostatistical framework in order to choose the best set of environmental and climatic covariates associated with the parasitaemia risk. Model validation confirmed that the ZIB model had a better predictive ability than the standard Binomial analogue. Markov chain Monte Carlo (MCMC) methods were used for inference. Several insecticide treated nets (ITN) coverage indicators were calculated to assess the effectiveness of interventions. After adjusting for climatic and socio-economic factors, the presence of at least one ITN per every two household members and living in urban areas reduced the odds of parasitaemia by 86% and 81% respectively. Posterior estimates of the ORs related to the wealth index show a decreasing trend with the quintiles. Infection odds appear to be increasing with age. The population-adjusted prevalence ranges from 0.12% in Thillé-Boubacar to 13.1% in Dabo. Tambacounda has the highest population-adjusted predicted prevalence (8.08%) whereas the region with the highest estimated number of infected children under the age of 5 years is Kolda (13940). The contemporary map and estimates of malaria burden identify the priority areas for future control interventions and provide baseline information for monitoring and evaluation. Zero-Inflated formulations are more appropriate in modeling sparse geostatistical survey data, expected to arise more frequently as malaria research is focused on elimination.

A national HIV/AIDS and malaria parasitological survey was carried out in Tanzania in 2007-2008. In this study the parasitological data were analyzed: i) to identify climatic/environmental, socio-economic and interventions factors associated with child malaria risk and ii) to produce a contemporary, high spatial resolution parasitaemia risk map of the country. Bayesian geostatistical models were fitted to assess the association between parasitaemia risk and its determinants. bayesian kriging was employed to predict malaria risk at unsampled locations across Tanzania and to obtain the uncertainty associated with the predictions. Markov chain Monte Carlo (MCMC) simulation methods were employed for model fit and prediction. Parasitaemia risk estimates were linked to population data and the number of infected children at province level was calculated. Model validation indicated a high predictive ability of the geostatistical model, with 60.00% of the test locations within the 95% credible interval. The results indicate that older children are significantly more likely to test positive for malaria compared with younger children and living in urban areas and better-off households reduces the risk of infection. However, none of the environmental and climatic proxies or the intervention measures were significantly associated with the risk of parasitaemia. Low levels of malaria prevalence were estimated for Zanzibar island. The population-adjusted prevalence ranges from 0.29% in Kaskazini province (Zanzibar island) to 18.65% in Mtwara region. The pattern of predicted malaria risk is similar with the previous maps based on historical data, although the estimates are lower. The predicted maps could be used by decision-makers to allocate resources and target interventions in the regions with highest burden of malaria in order to reduce the disease transmission in the country.

The 2006-2007 Angola Malaria Indicator Survey (AMIS) is the first nationally representative household survey in the country assessing coverage of the key malaria control interventions and measuring malaria-related burden among children under 5 years of age. In this paper, the Angolan MIS data were analyzed to produce the first smooth map of parasitaemia prevalence based on contemporary nationwide empirical data in the country. Bayesian geostatistical models were fitted to assess the effect of interventions after adjusting for environmental, climatic and socio-economic factors. Non-linear relationships between parasitaemia risk and environmental predictors were modeled by categorizing the covariates and by employing two non-parametric approaches, the B-splines and the P-splines. The results of the model validation showed that the categorical model was able to better capture the relationship between parasitaemia prevalence and the environmental factors. Model fit and prediction were handled within a Bayesian framework using Markov chain Monte Carlo (MCMC) simulations. Combining estimates of parasitaemia prevalence with the number of children under we obtained estimates of the number of infected children in the country. The population-adjusted prevalence ranges from in Namibe province to in Malanje province. The odds of parasitaemia in children living in a household with at least ITNs per person was by 41% lower (CI: 14%, 60%) than in those with fewer ITNs. The estimates of the number of parasitaemic children produced in this paper are important for planning and implementing malaria control interventions and for monitoring the impact of prevention and control activities.

BACKGROUND: Bovine tuberculosis (BTB) today primarily affects developing countries. In Africa, the disease is present essentially on the whole continent; however, little accurate information on its distribution and prevalence is available. Also, attempts to evaluate diagnostic tests for BTB in naturally infected cattle are scarce and mostly complicated by the absence of knowledge of the true disease status of the tested animals. However, diagnostic test evaluation in a given setting is a prerequisite for the implementation of local surveillance schemes and control measures. METHODOLOGY/PRINCIPAL FINDINGS: We subjected a slaughterhouse population of 954 Chadian cattle to single intra-dermal comparative cervical tuberculin (SICCT) testing and two recently developed fluorescence polarization assays (FPA). Using a Bayesian modeling approach we computed the receiver operating characteristic (ROC) curve of each diagnostic test, the true disease prevalence in the sampled population and the disease status of all sampled animals in the absence of knowledge of the true disease status of the sampled animals. In our Chadian setting, SICCT performed better if the cut-off for positive test interpretation was lowered from >4 mm (OIE standard cut-off) to >2 mm. Using this cut-off, SICCT showed a sensitivity and specificity of 66% and 89%, respectively. Both FPA tests showed sensitivities below 50% but specificities above 90%. The true disease prevalence was estimated at 8%. Altogether, 11% of the sampled animals showed gross visible tuberculous lesions. However, modeling of the BTB disease status of the sampled animals indicated that 72% of the suspected tuberculosis lesions detected during standard meat inspections were due to other pathogens than Mycobacterium bovis. CONCLUSIONS/SIGNIFICANCE: Our results have important implications for BTB diagnosis in a high incidence sub-Saharan African setting and demonstrate the practicability of our Bayesian approach for diagnostic test evaluation.

Influenza virosomes represent an innovative human-compatible antigen delivery system that has already proven its suitability for subunit vaccine design. The aim of the study was to proof the concept that virosomes can also be used to elicit high titers of antibodies against synthetic peptides. The specific objective was to demonstrate the safety and immunogenicity of two virosome-formulated P. falciparum protein derived synthetic peptide antigens given in two different doses alone or in combination.The design was a single blind, randomized, placebo controlled, dose-escalating study involving 46 healthy Caucasian volunteers aged 18-45 years. Five groups of 8 subjects received virosomal formulations containing 10 microg or 50 microg of AMA 49-CPE, an apical membrane antigen-1 (AMA-1) derived synthetic phospatidylethanolamine (PE)-peptide conjugate or 10 ug or 50 ug of UK39, a circumsporozoite protein (CSP) derived synthetic PE-peptide conjugate or 50 ug of both antigens each. A control group of 6 subjects received unmodified virosomes. Virosomal formulations of the antigens (designated PEV301 and PEV302 for the AMA-1 and the CSP virosomal vaccine, respectively) or unmodified virosomes were injected i. m. on days 0, 60 and 180. In terms of safety, no serious or severe adverse events (AEs) related to the vaccine were observed. 11/46 study participants reported 16 vaccine related local AEs. Of these 16 events, all being pain, 4 occurred after the 1(st), 7 after the 2(nd) and 5 after the 3(rd) vaccination. 6 systemic AEs probably related to the study vaccine were reported after the 1(st) injection, 10 after the 2(nd) and 6 after the 3(rd). Generally, no difference in the distribution of the systemic AEs between either the doses applied (10 respectively 50 microg) or the synthetic antigen vaccines (PEV301 and PEV302) used for immunization was found. In terms of immunogenicity, both PEV301 and PEV302 elicited already after two injections a synthetic peptide-specific antibody response in all volunteers immunized with the appropriate dose. In the case of PEV301 the 50 microg antigen dose was associated with a higher mean antibody titer and seroconversion rate than the 10 microg dose. In contrast, for PEV302 mean titer and seroconversion rate were higher with the lower dose. Combined delivery of PEV301 and PEV302 did not interfere with the development of an antibody response to either of the two antigens. No relevant antibody responses against the two malaria antigens were observed in the control group receiving unmodified virosomes.The present study demonstrates that three immunizations with the virosomal malaria vaccine components PEV301 or/and PEV302 (containing 10 microg or 50 microg of antigen) are safe and well tolerated. At appropriate antigen doses seroconversion rates of 100% were achieved. Two injections may be sufficient for eliciting an appropriate immune response, at least in individuals with pre-existing anti-malarial immunity. These results justify further development of a final multi-stage virosomal vaccine formulation incorporating additional malaria antigens.ClinicalTrials.gov NCT00400101.

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., Competing Interests: The authors have declared that no competing interests exist.

Introduction: The effect of malaria exposure on mortality using health facility incidence data as a measure of transmission has not been well investigated. Health and demographic surveillance systems (HDSS) routinely capture data on mortality, interventions and other household related indicators, offering a unique platform for estimating and monitoring the incidence-mortality relationship in space and time., Methods: Mortality data from the HDSS located in Western Kenya collected from 2007 to 2012 and linked to health facility incidence data were analysed using Bayesian spatio-temporal survival models to investigate the relation between mortality (all-cause/malaria-specific) and malaria incidence across all age groups. The analysis adjusted for insecticide-treated net (ITN) ownership, socio-economic status (SES), distance to health facilities and altitude. The estimates obtained were used to quantify excess mortality due to malaria exposure., Results: Our models identified a strong positive relationship between slide positivity rate (SPR) and all-cause mortality in young children 1-4 years (HR = 4.29; 95% CI: 2.78-13.29) and all ages combined (HR = 1.55; 1.04-2.80). SPR had a strong positive association with malaria-specific mortality in young children (HR = 9.48; 5.11-37.94), however, in older children (5-14 years), it was associated with a reduction in malaria specific mortality (HR = 0.02; 0.003-0.33)., Conclusion: SPR as a measure of transmission captures well the association between malaria transmission intensity and all-cause/malaria mortality. This offers a quick and efficient way to monitor malaria burden. Excess mortality estimates indicate that small changes in malaria incidence substantially reduce overall and malaria specific mortality.

Background: Malaria burden in Uganda has declined disproportionately among regions despite overall high intervention coverage across all regions. The Uganda Malaria Indicator Survey (MIS) 2014-15 was the second nationally representative survey conducted to provide estimates of malaria prevalence among children less than 5 years, and to track the progress of control interventions in the country. In this present study, 2014-15 MIS data were analysed to assess intervention effects on malaria prevalence in Uganda among children less than 5 years, assess intervention effects at regional level, and estimate geographical distribution of malaria prevalence in the country., Methods: Bayesian geostatistical models with spatially varying coefficients were used to determine the effect of interventions on malaria prevalence at national and regional levels. Spike-and-slab variable selection was used to identify the most important predictors and forms. Bayesian kriging was used to predict malaria prevalence at unsampled locations., Results: Indoor Residual Spraying (IRS) and Insecticide Treated Nets (ITN) ownership had a significant but varying protective effect on malaria prevalence. However, no effect was observed for Artemisinin Combination-based Therapies (ACTs). Environmental factors, namely, land cover, rainfall, day and night land surface temperature, and area type were significantly associated with malaria prevalence. Malaria prevalence was higher in rural areas, increased with the child's age, and decreased with higher household socioeconomic status and higher level of mother's education. The highest prevalence of malaria in children less than 5 years was predicted for regions of East Central, North East and West Nile, whereas the lowest was predicted in Kampala and South Western regions, and in the mountainous areas in Mid-Western and Mid-Eastern regions., Conclusions: IRS and ITN ownership are important interventions against malaria prevalence in children less than 5 years in Uganda. The varying effects of the interventions calls for selective implementation of control tools suitable to regional ecological settings. To further reduce malaria burden and sustain malaria control in Uganda, current tools should be supplemented by health system strengthening, and socio-economic development.

Introduction: With the renewed drive towards malaria elimination, there is a need for improved surveillance tools. While time series analysis is an important tool for surveillance, prediction and for measuring interventions' impact, approximations by commonly used Gaussian methods are prone to inaccuracies when case counts are low. Therefore, statistical methods appropriate for count data are required, especially during "consolidation" and "pre-elimination" phases., Methods: Generalized autoregressive moving average (GARMA) models were extended to generalized seasonal autoregressive integrated moving average (GSARIMA) models for parsimonious observation-driven modelling of non Gaussian, non stationary and/or seasonal time series of count data. The models were applied to monthly malaria case time series in a district in Sri Lanka, where malaria has decreased dramatically in recent years., Results: The malaria series showed long-term changes in the mean, unstable variance and seasonality. After fitting negative-binomial Bayesian models, both a GSARIMA and a GARIMA deterministic seasonality model were selected based on different criteria. Posterior predictive distributions indicated that negative-binomial models provided better predictions than Gaussian models, especially when counts were low. The G(S)ARIMA models were able to capture the autocorrelation in the series., Conclusions: G(S)ARIMA models may be particularly useful in the drive towards malaria elimination, since episode count series are often seasonal and non-stationary, especially when control is increased. Although building and fitting GSARIMA models is laborious, they may provide more realistic prediction distributions than do Gaussian methods and may be more suitable when counts are low.

A national HIV/AIDS and malaria parasitological survey was carried out in Tanzania in 2007-2008. In this study the parasitological data were analyzed: i) to identify climatic/environmental, socio-economic and interventions factors associated with child malaria risk and ii) to produce a contemporary, high spatial resolution parasitaemia risk map of the country. Bayesian geostatistical models were fitted to assess the association between parasitaemia risk and its determinants. bayesian kriging was employed to predict malaria risk at unsampled locations across Tanzania and to obtain the uncertainty associated with the predictions. Markov chain Monte Carlo (MCMC) simulation methods were employed for model fit and prediction. Parasitaemia risk estimates were linked to population data and the number of infected children at province level was calculated. Model validation indicated a high predictive ability of the geostatistical model, with 60.00% of the test locations within the 95% credible interval. The results indicate that older children are significantly more likely to test positive for malaria compared with younger children and living in urban areas and better-off households reduces the risk of infection. However, none of the environmental and climatic proxies or the intervention measures were significantly associated with the risk of parasitaemia. Low levels of malaria prevalence were estimated for Zanzibar island. The population-adjusted prevalence ranges from 0.29% in Kaskazini province (Zanzibar island) to 18.65% in Mtwara region. The pattern of predicted malaria risk is similar with the previous maps based on historical data, although the estimates are lower. The predicted maps could be used by decision-makers to allocate resources and target interventions in the regions with highest burden of malaria in order to reduce the disease transmission in the country.

The Research Center for Human Development in Dakar (CRDH) with the technical assistance of ICF Macro and the National Malaria Control Programme (NMCP) conducted in 2008/2009 the Senegal Malaria Indicator Survey (SMIS), the first nationally representative household survey collecting parasitological data and malaria-related indicators. In this paper, we present spatially explicit parasitaemia risk estimates and number of infected children below 5 years. Geostatistical Zero-Inflated Binomial models (ZIB) were developed to take into account the large number of zero-prevalence survey locations (70%) in the data. Bayesian variable selection methods were incorporated within a geostatistical framework in order to choose the best set of environmental and climatic covariates associated with the parasitaemia risk. Model validation confirmed that the ZIB model had a better predictive ability than the standard Binomial analogue. Markov chain Monte Carlo (MCMC) methods were used for inference. Several insecticide treated nets (ITN) coverage indicators were calculated to assess the effectiveness of interventions. After adjusting for climatic and socio-economic factors, the presence of at least one ITN per every two household members and living in urban areas reduced the odds of parasitaemia by 86% and 81% respectively. Posterior estimates of the ORs related to the wealth index show a decreasing trend with the quintiles. Infection odds appear to be increasing with age. The population-adjusted prevalence ranges from 0.12% in Thillé-Boubacar to 13.1% in Dabo. Tambacounda has the highest population-adjusted predicted prevalence (8.08%) whereas the region with the highest estimated number of infected children under the age of 5 years is Kolda (13940). The contemporary map and estimates of malaria burden identify the priority areas for future control interventions and provide baseline information for monitoring and evaluation. Zero-Inflated formulations are more appropriate in modeling sparse geostatistical survey data, expected to arise more frequently as malaria research is focused on elimination.

The 2006-2007 Angola Malaria Indicator Survey (AMIS) is the first nationally representative household survey in the country assessing coverage of the key malaria control interventions and measuring malaria-related burden among children under 5 years of age. In this paper, the Angolan MIS data were analyzed to produce the first smooth map of parasitaemia prevalence based on contemporary nationwide empirical data in the country. Bayesian geostatistical models were fitted to assess the effect of interventions after adjusting for environmental, climatic and socio-economic factors. Non-linear relationships between parasitaemia risk and environmental predictors were modeled by categorizing the covariates and by employing two non-parametric approaches, the B-splines and the P-splines. The results of the model validation showed that the categorical model was able to better capture the relationship between parasitaemia prevalence and the environmental factors. Model fit and prediction were handled within a Bayesian framework using Markov chain Monte Carlo (MCMC) simulations. Combining estimates of parasitaemia prevalence with the number of children under we obtained estimates of the number of infected children in the country. The population-adjusted prevalence ranges from in Namibe province to in Malanje province. The odds of parasitaemia in children living in a household with at least ITNs per person was by 41% lower (CI: 14%, 60%) than in those with fewer ITNs. The estimates of the number of parasitaemic children produced in this paper are important for planning and implementing malaria control interventions and for monitoring the impact of prevention and control activities.

Background: Bovine tuberculosis (BTB) today primarily affects developing countries. In Africa, the disease is present essentially on the whole continent; however, little accurate information on its distribution and prevalence is available. Also, attempts to evaluate diagnostic tests for BTB in naturally infected cattle are scarce and mostly complicated by the absence of knowledge of the true disease status of the tested animals. However, diagnostic test evaluation in a given setting is a prerequisite for the implementation of local surveillance schemes and control measures., Methodology/principal Findings: We subjected a slaughterhouse population of 954 Chadian cattle to single intra-dermal comparative cervical tuberculin (SICCT) testing and two recently developed fluorescence polarization assays (FPA). Using a Bayesian modeling approach we computed the receiver operating characteristic (ROC) curve of each diagnostic test, the true disease prevalence in the sampled population and the disease status of all sampled animals in the absence of knowledge of the true disease status of the sampled animals. In our Chadian setting, SICCT performed better if the cut-off for positive test interpretation was lowered from >4 mm (OIE standard cut-off) to >2 mm. Using this cut-off, SICCT showed a sensitivity and specificity of 66% and 89%, respectively. Both FPA tests showed sensitivities below 50% but specificities above 90%. The true disease prevalence was estimated at 8%. Altogether, 11% of the sampled animals showed gross visible tuberculous lesions. However, modeling of the BTB disease status of the sampled animals indicated that 72% of the suspected tuberculosis lesions detected during standard meat inspections were due to other pathogens than Mycobacterium bovis., Conclusions/significance: Our results have important implications for BTB diagnosis in a high incidence sub-Saharan African setting and demonstrate the practicability of our Bayesian approach for diagnostic test evaluation.

Background and Objectives: Influenza virosomes represent an innovative human-compatible antigen delivery system that has already proven its suitability for subunit vaccine design. The aim of the study was to proof the concept that virosomes can also be used to elicit high titers of antibodies against synthetic peptides. The specific objective was to demonstrate the safety and immunogenicity of two virosome-formulated P. falciparum protein derived synthetic peptide antigens given in two different doses alone or in combination., Methodology/principal Findings: The design was a single blind, randomized, placebo controlled, dose-escalating study involving 46 healthy Caucasian volunteers aged 18-45 years. Five groups of 8 subjects received virosomal formulations containing 10 microg or 50 microg of AMA 49-CPE, an apical membrane antigen-1 (AMA-1) derived synthetic phospatidylethanolamine (PE)-peptide conjugate or 10 ug or 50 ug of UK39, a circumsporozoite protein (CSP) derived synthetic PE-peptide conjugate or 50 ug of both antigens each. A control group of 6 subjects received unmodified virosomes. Virosomal formulations of the antigens (designated PEV301 and PEV302 for the AMA-1 and the CSP virosomal vaccine, respectively) or unmodified virosomes were injected i. m. on days 0, 60 and 180. In terms of safety, no serious or severe adverse events (AEs) related to the vaccine were observed. 11/46 study participants reported 16 vaccine related local AEs. Of these 16 events, all being pain, 4 occurred after the 1(st), 7 after the 2(nd) and 5 after the 3(rd) vaccination. 6 systemic AEs probably related to the study vaccine were reported after the 1(st) injection, 10 after the 2(nd) and 6 after the 3(rd). Generally, no difference in the distribution of the systemic AEs between either the doses applied (10 respectively 50 microg) or the synthetic antigen vaccines (PEV301 and PEV302) used for immunization was found. In terms of immunogenicity, both PEV301 and PEV302 elicited already after two injections a synthetic peptide-specific antibody response in all volunteers immunized with the appropriate dose. In the case of PEV301 the 50 microg antigen dose was associated with a higher mean antibody titer and seroconversion rate than the 10 microg dose. In contrast, for PEV302 mean titer and seroconversion rate were higher with the lower dose. Combined delivery of PEV301 and PEV302 did not interfere with the development of an antibody response to either of the two antigens. No relevant antibody responses against the two malaria antigens were observed in the control group receiving unmodified virosomes., Conclusions: The present study demonstrates that three immunizations with the virosomal malaria vaccine components PEV301 or/and PEV302 (containing 10 microg or 50 microg of antigen) are safe and well tolerated. At appropriate antigen doses seroconversion rates of 100% were achieved. Two injections may be sufficient for eliciting an appropriate immune response, at least in individuals with pre-existing anti-malarial immunity. These results justify further development of a final multi-stage virosomal vaccine formulation incorporating additional malaria antigens., Trial Registration: ClinicalTrials.gov NCT00400101.