The soil-transmitted threadworm, Strongyloides stercoralis, is one of the most neglected among the so-called neglected tropical diseases (NTDs). We reviewed studies of the last 20 years on S. stercoralis's global prevalence in general populations and risk groups. A literature search was performed in PubMed for articles published between January 1989 and October 2011. Articles presenting information on infection prevalence were included. A Bayesian meta-analysis was carried out to obtain country-specific prevalence estimates and to compare disease odds ratios in different risk groups taking into account the sensitivities of the diagnostic methods applied. A total of 354 studies from 78 countries were included for the prevalence calculations, 194 (62.4%) were community-based studies, 121 (34.2%) were hospital-based studies and 39 (11.0%) were studies on refugees and immigrants. World maps with country data are provided. In numerous African, Asian and South-American resource-poor countries, information on S. stercoralis is lacking. The meta-analysis showed an association between HIV-infection/alcoholism and S. stercoralis infection (OR: 2.17 BCI: 1.18–4.01; OR: 6.69; BCI: 1.47–33.8), respectively. Our findings show high infection prevalence rates in the general population in selected countries and geographical regions. S. stercoralis infection is prominent in several risk groups. Adequate information on the prevalence is still lacking from many countries. However, current information underscore that S. stercoralis must not be neglected. Further assessments in socio-economic and ecological settings are needed and integration into global helminth control is warranted. The soil-transmitted threadworm Strongyloides stercoralis is one of the most neglected helminth infections. It is endemic world-wide, yet more prevalent in hot and humid climates as well as resource poor countries with inadequate sanitary conditions. The difficult diagnosis and irregular excretion of larvae lead to an underreporting of infection rates. We reviewed the literature of the last 20 years reporting on infection rates of S. stercoralis. Including the sensitivity of diagnostic methods applied, we modeled and mapped for the first time country-wide prevalence estimates. The modeling was divided into studies reporting infection rates in the general population, in hospitals and on refugees & immigrants, respectively. We further summarized possible risk factors for S. stercoralis infection using meta-analysis. The most prominent risk factors include HIV-infection, HTLV-1 infection and alcoholism. Information on infection rates is missing in many countries. Our results show high prevalence estimates in many resource poor tropical and subtropical countries. We conclude that S. stercoralis should not be neglected and that further studies applying high sensitivity diagnostic methods are needed.

Multidrug resistant (MDR) bacteria are a growing threat to global health. Studies focusing on single antibiotics have shown that drug resistance is often associated with a fitness cost in the absence of drug. However, little is known about the fitness cost associated with resistance to multiple antibiotics. We used Mycobacterium smegmatis as a model for human tuberculosis (TB) and an in vitro competitive fitness assay to explore the combined fitness effects and interaction between mutations conferring resistance to rifampicin (RIF) and ofloxacin (OFX); two of the most important first- and second-line anti-TB drugs, respectively. We found that 4 out of 17 M. smegmatis mutants (24%) resistant to RIF and OFX showed a statistically significantly higher or lower competitive fitness than expected when assuming a multiplicative model of fitness effects of each individual mutation. Moreover, 6 out of the 17 double drug-resistant mutants (35%) had a significantly higher fitness than at least one of the corresponding single drug-resistant mutants. The particular combinations of resistance mutations associated with no fitness deficit in M. smegmatis were the most frequent among 151 clinical isolates of MDR and extensively drug-resistant (XDR) Mycobacterium tuberculosis from South Africa. Our results suggest that epistasis between drug resistance mutations in mycobacteria can lead to MDR strains with no fitness deficit, and that these strains are positively selected in settings with a high burden of drug-resistant TB. Taken together, our findings support a role for epistasis in the evolution and epidemiology of MDR- and XDR-TB.

In the past decade, decreases in clinical episodes and deaths due to malaria have been mainly associated with the expansion of vector-control measures, such as insecticide-treated bednets and indoor residual spraying. Malaria indicator surveys gather information about key malaria indicators through national representative household surveys. We aimed to estimate changes in risk of malaria parasitaemia at high spatial resolution in sub-Saharan Africa, and to quantify the effects of malaria interventions at national and subnational levels. In this spatial and temporal analysis, we analysed data from the six sub-Saharan countries that had publicly available data from two malaria indicator or demographic and health surveys with malaria measurements done in 2006-08 and 2010-12: Angola, Liberia, Mozambique, Senegal, Rwanda, and Tanzania. We used Bayesian geostatistical models to estimate the present malaria risk and to establish the change relative to the period between the last two national surveys. We applied Bayesian variable selection procedures to select the most relevant insecticide-treated-bednet measure for reducing malaria risk, and did spatial kriging over the study region to produce intervention coverage maps. We estimated the contribution of bednets and indoor residual spraying on changes in malaria risk, after adjustment for climatic and socioeconomic factors. Spatially varying coefficients of intervention coverage enabled estimation of their effects at subnational level. In all countries, the probability of decrease in parasitaemia varied substantially between regions. Insecticide-treated bednets were an important intervention for reducing malaria risk, according to different definitions of coverage. An overall effect of insecticide-treated bednets at country level was significant only in Angola (-0·64, 95% credible interval -0·98 to -0·30) and Senegal (-0·34, -0·64 to -0·05); however, in all countries, we detected significant effects of bednets and indoor residual spraying at local level. The described methodology is useful for the identification of regions where changes in malaria risk have taken place, and to describe the geographical pattern of malaria. Intervention effects vary in space, which might be driven by local endemicity levels. The produced maps provide a visual aid for national malaria control programmes to identify where targeted strategies and resources are most needed or likely to have the greatest effect on reducing the risk of parasitaemia.

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.

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.