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Highly virulent strains of Clostridium difficile have emerged since 2003, causing large outbreaks of severe, often fatal, colitis in North America and Europe. In 2008–10, virulent strains spread between continents, with the first reported cases of fluoroquinolone-resistant C difficile PCR ribotype 027 in three Asia-Pacific countries and Central America. We present a risk assessment framework for assessing risks of further worldwide spread of this pathogen. This framework first requires identification of potential vehicles of introduction, including international transfers of hospital patients, international tourism and migration, and trade in livestock, associated commodities, and foodstuffs. It then calls for assessment of the risks of pathogen release, of exposure of individuals if release happens, and of resulting outbreaks. Health departments in countries unaffected by outbreaks should assess the risk of introduction or reintroduction of C difficile PCR ribotype 027 using a structured risk-assessment approach.

Background Malaria remains a significant health problem in Bangladesh affecting 13 of 64 districts. The risk of malaria is variable across the endemic areas and throughout the year. A better understanding of the spatial and temporal patterns in malaria risk and the determinants driving the variation are crucial for the appropriate targeting of interventions under the National Malaria Control and Prevention Programme. Methods Numbers of Plasmodium falciparum and Plasmodium vivax malaria cases reported by month in 2007, across the 70 endemic thanas (sub-districts) in Bangladesh, were assembled from health centre surveillance reports. Bayesian Poisson regression models of incidence were constructed, with fixed effects for monthly rainfall, maximum temperature and elevation, and random effects for thanas , with a conditional autoregressive prior spatial structure. Results The annual incidence of reported cases was 34.0 and 9.6 cases/10,000 population for P. falciparum and P. vivax respectively and the population of the 70 malaria-endemic thanas was approximately 13.5 million in 2007. Incidence of reported cases for both types of malaria was highest in the mountainous south-east of the country (the Chittagong Hill Tracts). Models revealed statistically significant positive associations between the incidence of reported P. vivax and P. falciparum cases and rainfall and maximum temperature. Conclusions The risk of P. falciparum and P. vivax was spatially variable across the endemic thanas of Bangladesh and also highly seasonal, suggesting that interventions should be targeted and timed according to the risk profile of the endemic areas. Rainfall, temperature and elevation are major factors driving the spatiotemporal patterns of malaria in Bangladesh.

Malaria is one of the biggest contributors to deaths caused by infectious disease. More than 30 countries have planned or started programmes to target malaria elimination, often with explicit support from international donors. The spatial distribution of malaria, at all levels of endemicity, is heterogeneous. Moreover, populations living in low-endemic settings where elimination efforts might be targeted are often spatially heterogeneous. Geospatial methods, therefore, can help design, target, monitor, and assess malaria elimination programmes. Rapid advances in technology and analytical methods have allowed the spatial prediction of malaria risk and the development of spatial decision support systems, which can enhance elimination programmes by enabling accurate and timely resource allocation. However, no framework exists for assessment of geospatial instruments. Research is needed to identify measurable indicators of elimination progress and to quantify the effect of geospatial methods in achievement of elimination outcomes.

Background Reliable and updated maps of helminth (worm) infection distributions are essential to target control strategies to those populations in greatest need. Although many surveys have been conducted in endemic countries, the data are rarely available in a form that is accessible to policy makers and the managers of public health programmes. This is especially true in sub-Saharan Africa, where empirical data are seldom in the public domain. In an attempt to address the paucity of geographical information on helminth risk, this article describes the development of an updated global atlas of human helminth infection, showing the example of East Africa. Methods Empirical, cross-sectional estimates of infection prevalence conducted since 1980 were identified using electronic and manual search strategies of published and unpublished sources. A number of inclusion criteria were imposed for identified information, which was extracted into a standardized database. Details of survey population, diagnostic methods, sample size and numbers infected with schistosomes and soil-transmitted helminths were recorded. A unique identifier linked each record to an electronic copy of the source document, in portable document format. An attempt was made to identify the geographical location of each record using standardized geolocation procedures and the assembled data were incorporated into a geographical information system. Results At the time of writing, over 2,748 prevalence surveys were identified through multiple search strategies. Of these, 2,612 were able to be geolocated and mapped. More than half (58%) of included surveys were from grey literature or unpublished sources, underlining the importance of reviewing in-country sources. 66% of all surveys were conducted since 2000. Comprehensive, countrywide data are available for Burundi, Rwanda and Uganda. In contrast, information for Kenya and Tanzania is typically clustered in specific regions of the country, with few records from areas with very low population density and/or environmental conditions which are unfavourable for helminth transmission. Information is presented on the prevalence and geographical distribution for the major helminth species. Conclusion For all five countries, the information assembled in the current atlas provides the most reliable, up-to-date and comprehensive source of data on the distribution of common helminth infections to guide the rational implementation of control efforts.

Health system and environmental factors play a significant role in achieving the World Health Organization (WHO) End Tuberculosis (TB) targets. However, quantitative measures are scarce or non-existent at a global level. We aimed to measure the progress made towards meeting the global End TB milestones from 2015 to 2020 and identify health system and environmental factors contributing to the success. We obtained data from ten different online data repositories and used principal component analysis to create domain-specific health system performance measures. We used radar charts and dumbbell plots to show the country's progress in ending TB with their health systems. Lastly, we used a linear regression model to identify key health systems and environmental predictors of the percent reduction in TB incidence and mortality. There was a high variation in TB incidence and mortality reduction between countries and WHO regions. Of all countries included, 75 (39.3%) achieved more than a 20% reduction in TB incidence between 2015 and 2020. However, only 31 (16.2%) reached a 35% reduction in TB mortality. The European Region achieved the highest incidence reduction, exceeding the 2020 milestone with a 25% reduction. The African Region also made notable progress, achieving an 18% mortality reduction despite its relatively poor health systems. Health system factors, such as TB financing, TB-specific health service delivery, access to medicine, and governance, were significantly associated with TB mortality reduction between 2015 and 2020. Environmental factors, such as average annual temperature and air particulate matter concentration, were found to have a significant negative effect on TB incidence and mortality reduction. Weak health systems were identified as major barriers to achieving the End TB milestones in most high-burden countries. Hence, strengthening health systems with a special focus on TB financing, service delivery, and access to medicine in these countries should be prioritised to achieve global TB mortality reduction targets. Countries should follow WHO's air quality guidelines and rapidly reduce carbon dioxide and other greenhouse gas emissions to mitigate the impact of environmental factors.

Background The Ministry of Health in the Republic of Vanuatu has implemented a malaria elimination programme in Tafea Province, the most southern and eastern limit of malaria transmission in the South West Pacific. Tafea Province is comprised of five islands with malaria elimination achieved on one of these islands (Aneityum) in 1998. The current study aimed to establish the baseline distribution of malaria on the most malarious of the province's islands, Tanna Island, to guide the implementation of elimination activities. Methods A parasitological survey was conducted in Tafea Province in 2008. On Tanna Island there were 4,716 participants from 220 villages, geo-referenced using a global position system. Spatial autocorrelation in observed prevalence values was assessed using a semivariogram. Backwards step-wise regression analysis was conducted to determine the inclusion of environmental and climatic variables into a prediction model. The Bayesian geostatistical logistic regression model was used to predict malaria risk, and associated uncertainty across the island. Results Overall, prevalence on Tanna was 1.0% for Plasmodium falciparum (accounting for 32% of infections) and 2.2% for Plasmodium vivax (accounting for 68% of infections). Regression analysis showed significant association with elevation and distance to coastline for P. vivax and P. falciparum , but no significant association with NDVI or TIR. Colinearity was observed between elevation and distance to coastline with the later variable included in the final Bayesian geostatistical model for P. vivax and the former included in the final model for P. falciparum . Model validation statistics revealed that the final Bayesian geostatistical model had good predictive ability. Conclusion Malaria in Tanna Island, Vanuatu, has a focal and predominantly coastal distribution. As Vanuatu refines its elimination strategy, malaria risk maps represent an invaluable resource in the strategic planning of all levels of malaria interventions for the island.

Background Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden. Methods We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ). Results We identified 168 eligible studies with spatial methods used to describe the spatial distribution ( n  = 154), spatial clusters ( n  = 73), predictors of spatial patterns ( n  = 64), the role of congregate settings ( n  = 3) and the household ( n  = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff’s spatial scan statistic followed by local Moran’s I and Getis and Ord’s local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined. Conclusions A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

Background To describe spatiotemporal patterns of diarrhoea in Bhutan, and quantify the association between climatic factors and the distribution and dynamics of the disease. Methods Nationwide data on diarrhoea were obtained for 2003 to 2013 from the Health Information and Management System (HIMS), Ministry of Health, Bhutan. Climatic variables were obtained from the Department of Hydro Met Services, Ministry of Economic Affairs, Bhutan. Seasonal trend decomposition was used to examine secular trends and seasonal patterns of diarrhoea. A Bayesian conditional autoregressive (CAR) model was used to quantify the relationship between monthly diarrhoea, maximum temperature, rainfall, age and gender. Results The monthly average diarrhoea incidence was highly seasonal. Diarrhoea incidence increased by 0.6% (95% CrI: 0.5–0.6%) for every degree increase in maximum temperature; and 5% (95 Cr I: 4.9–5.1%) for a 1 mm increase in rainfall. Children aged <5 years were found to be 74.2% (95% CrI: 74.1–74.4) more likely to experience diarrhoea than children and adults aged ≥5 years and females were 4.9% (95% CrI: 4.4–5.3%) less likely to suffer from diarrhoea as compared to males. Significant residual spatial clustering was found after accounting for climate and demographic variables. Conclusions Diarrhoea incidence was highly seasonal, with positive associations with maximum temperature and rainfall and negative associations with age and being female. This calls for public health actions to reduce future risks of climate change with great consideration of local climatic conditions. In addition, protection of <5 years children should be prioritize through provision of rotavirus vaccination, safe and clean drinking water, and proper latrines.

Background Malaria is a major public health burden in Southeastern Bangladesh, particularly in the Chittagong Hill Tracts region. Malaria is endemic in 13 districts of Bangladesh and the highest prevalence occurs in Khagrachari (15.47%). Methods A risk map was developed and geographic risk factors identified using a Bayesian approach. The Bayesian geostatistical model was developed from previously identified individual and environmental covariates (p < 0.2; age, different forest types, elevation and economic status) for malaria prevalence using WinBUGS 1.4. Spatial correlation was estimated within a Bayesian framework based on a geostatistical model. The infection status (positives and negatives) was modeled using a Bernoulli distribution. Maps of the posterior distributions of predicted prevalence were developed in geographic information system (GIS). Results Predicted high prevalence areas were located along the north-eastern areas, and central part of the study area. Low to moderate prevalence areas were predicted in the southwestern, southeastern and central regions. Individual age and nearness to fragmented forest were associated with malaria prevalence after adjusting the spatial auto-correlation. Conclusion A Bayesian analytical approach using multiple enabling technologies (geographic information systems, global positioning systems, and remote sensing) provide a strategy to characterize spatial heterogeneity in malaria risk at a fine scale. Even in the most hyper endemic region of Bangladesh there is substantial spatial heterogeneity in risk. Areas that are predicted to be at high risk, based on the environment but that have not been reached by surveys are identified.

Mass drug administration (MDA) of albendazole to at-risk populations remains the primary strategy for controlling soil-transmitted helminths (STH). Despite its widely use, its efficacy varies among different STH species and remains sub-optimal, particularly in the treatment of T. trichiura . Currently, studies investigating the optimal dose and regimens for albendazole are lacking. A longitudinal cohort study was conducted to assess the efficacy of two single-dose albendazole 400 mg treatments given four weeks apart targeting STH infections compared with just one single-dose albendazole 400 mg on 375 schoolchildren in Bulang Shan, Menghai county, Yunnan Province, China from October to December 2015. The first round of albendazole resulted in cure rates (CR) of 92.5%, 63.1% and 5.1%, and egg reduction rates (ERR) of 99.2%, 87.9% and 41.1% for A. lumbricoides , hookworms and T. trichiura , respectively. With the second round, efficacy remains high against A. lumbricoides (98.9% CR), is increased against hookworm (92.2% CR), and remains low against T. trichiura (6.3% CR). The second round increased the ERR to 99.6%, 99.8% and 74.1% for the same species, respectively. In this setting, albendazole is thus highly effective against A. lumbricoides , reasonably effective against hookworm, but has low efficacy against T. trichiura following two rounds of treatment. A cohort study of schoolchildren in Yunnan Province, China showed that the two rounds of 400 mg albendazole treatment were highly effective against Ascaris lumbricoides, moderately effective for hookworm, and ineffective for Trichuris trichiura.