Surveillance systems for neglected tropical diseases: global lessons from China's evolving schistosomiasis reporting systems, 1949-2014

How do disease control measures impact spatial predictions of schistosomiasis and hookworm? The example of predicting school-based prevalence before and after preventive chemotherapy in Ghana

BACKGROUND

Schistosomiasis and soil-transmitted helminth infections are among the neglected tropical diseases (NTDs) affecting primarily marginalized communities in low- and middle-income countries. Surveillance data for NTDs are typically sparse, and hence, geospatial predictive modeling based on remotely sensed (RS) environmental data is widely used to characterize disease transmission and treatment needs. However, as large-scale preventive chemotherapy has become a widespread practice, resulting in reduced prevalence and intensity of infection, the validity and relevance of these models should be re-assessed.

METHODOLOGY

We employed two nationally representative school-based prevalence surveys of Schistosoma haematobium and hookworm infections from Ghana conducted before (2008) and after (2015) the introduction of large-scale preventive chemotherapy. We derived environmental variables from fine-resolution RS data (Landsat 8) and examined a variable distance radius (1-5 km) for aggregating these variables around point-prevalence locations in a non-parametric random forest modeling approach. We used partial dependence and individual conditional expectation plots to improve interpretability.

PRINCIPAL FINDINGS

The average school-level S. haematobium prevalence decreased from 23.8% to 3.6% and that of hookworm from 8.6% to 3.1% between 2008 and 2015. However, hotspots of high-prevalence locations persisted for both diseases. The models with environmental data extracted from a buffer radius of 2-3 km around the school location where prevalence was measured had the best performance. Model performance (according to the R2 value) was already low and declined further from approximately 0.4 in 2008 to 0.1 in 2015 for S. haematobium and from approximately 0.3 to 0.2 for hookworm. According to the 2008 models, land surface temperature (LST), modified normalized difference water index (MNDWI), elevation, slope, and streams variables were associated with S. haematobium prevalence. LST, slope, and improved water coverage were associated with hookworm prevalence. Associations with the environment in 2015 could not be evaluated due to low model performance.

CONCLUSIONS/SIGNIFICANCE

Our study showed that in the era of preventive chemotherapy, associations between S. haematobium and hookworm infections and the environment weakened, and thus predictive power of environmental models declined. In light of these observations, it is timely to develop new cost-effective passive surveillance methods for NTDs as an alternative to costly surveys, and to focus on persisting hotspots of infection with additional interventions to reduce reinfection. We further question the broad application of RS-based modeling for environmental diseases for which large-scale pharmaceutical interventions are in place.

Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination

BACKGROUND

Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence.

METHODS

In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data.

RESULTS

The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen's kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (an indicator of surface water presence) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways.

CONCLUSION

Our results suggest that in low-transmission environments, leveraging open-source environmental data can yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Characteristics of leptospirosis cases, prevention and control managements 1955-2020, Guangzhou, China

Background

Leptospirosis, which is an easily overlooked zoonotic disease, was once widespread in Guangzhou, China. However, due to the implementation of control measures, the number of cases is decreasing. Based on the characteristics of leptospirosis cases in Guangzhou, China, between 1955 and 2020, we describe the changes and achievements in prevention and control management strategies over that period.

Methods

The development of the leptospirosis control system in Guangzhou occurred over three periods: Period I: 1955-1978; Period II: 1979-2000; and Period III: 2001-2020. Data about leptospirosis cases were obtained from the Guangzhou Center for Disease Control and Prevention (CDC) and national health departments. The demographic characteristics of leptospirosis patients were analyzed using descriptive statistics.

Results

During Period I, only the Guangzhou CDC and medical institutions at every level participated in the leptospirosis control system. During Period II, additional types of organizations, including local CDCs, countryside committees, community committees, and the Patriotic Health Movement Commission, were involved in the control system. Additionally, strong links were established between different organizations. After entering Period III, an increasing number of departments joined the cooperation, and the management of human patients was expanded to include the management of host animals, and thus, the prevalence of leptospirosis was monitored and controlled in various ways. The leptospirosis control system in Guangzhou has been further improved. From 1955 to 2020, a total of 2501 leptospirosis cases were recorded in Guangzhou, and the number of cases decreased significantly over time, from 1608 (Period I) to 744 (Period II) and then to 149 (Period III).

Conclusion

The improvements of the leptospirosis control system in Guangzhou that occurred over decades were associated with a marked decrease in the number of leptospirosis cases. Guangzhou's experience can provide guidance for other countries or cities around the world facing similar challenges.

Optimizing laboratory-based surveillance networks for monitoring multi-genotype or multi-serotype infections

With the aid of laboratory typing techniques, infectious disease surveillance networks have the opportunity to obtain powerful information on the emergence, circulation, and evolution of multiple genotypes, serotypes or other subtypes of pathogens, informing understanding of transmission dynamics and strategies for prevention and control. The volume of typing performed on clinical isolates is typically limited by its ability to inform clinical care, cost and logistical constraints, especially in comparison with the capacity to monitor clinical reports of disease occurrence, which remains the most widespread form of public health surveillance. Viewing clinical disease reports as arising from a latent mixture of pathogen subtypes, laboratory typing of a subset of clinical cases can provide inference on the proportion of clinical cases attributable to each subtype (i.e., the mixture components). Optimizing protocols for the selection of isolates for typing by weighting specific subpopulations, locations, time periods, or case characteristics (e.g., disease severity), may improve inference of the frequency and distribution of pathogen subtypes within and between populations. Here, we apply the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework to simulate and optimize hand foot and mouth disease (HFMD) surveillance in a high-burden region of western China. We identify laboratory surveillance designs that significantly outperform the existing network: the optimal network reduced mean absolute error in estimated serotype-specific incidence rates by 14.1%; similarly, the optimal network for monitoring severe cases reduced mean absolute error in serotype-specific incidence rates by 13.3%. In both cases, the optimal network designs achieved improved inference without increasing subtyping effort. We demonstrate how the DIOS framework can be used to optimize surveillance networks by augmenting clinical diagnostic data with limited laboratory typing resources, while adapting to specific, local surveillance objectives and constraints.

Care-seeking delay of imported malaria to China: implications for improving post-travel healthcare for migrant workers

BACKGROUND

Imported malaria cases continue to pose major challenges in China as well as in other countries having achieved elimination. Our study aims to identify the factors influencing the timing of care-seeking after symptom onset among migrant workers with imported malaria, in order to develop innovative interventions to improve access and provision of post-travel healthcare for returning migrants.

METHODS

We analysed the timing and types of healthcare service utilization after symptom onset among patients with imported malaria between 2012 and 2019 in Jiangsu Province, China. Moreover, decision tree models were used to explore the factors influencing the care-seeking timing after symptom onset among patients with imported malaria.

RESULTS

A total of 2255 cases of imported malaria were identified from 1 June 2012 through 31 December 2019. Patients with malaria imported into China were mainly male migrant labourers returning from sub-Saharan Africa (96.8%). A substantial number of patients with imported malaria sought healthcare >3 days after symptom onset, which clearly represented delayed healthcare-seeking behaviour. According to the decision tree analysis, initial healthcare seeking from healthcare facilities at higher administrative levels, infection with Plasmodium vivax and absence of malaria infection history were significantly associated with delayed healthcare seeking in patients with imported malaria.

CONCLUSION

The delay in seeking of medical care among migrant workers with imported malaria should be considered and addressed by specific interventions. In addition to increasing awareness about these issues among health care professionals, improved access to healthcare facilities at higher administrative levels as well as improved diagnostic capacity of healthcare facilities at lower administrative levels should be developed. Moreover, education programs targeting populations at risk of malaria importation and delayed healthcare seeking should be improved to facilitate early healthcare seeking and service use.

Novel tools and strategies for breaking schistosomiasis transmission: study protocol for an intervention study

Background

Global elimination of schistosomiasis as a public health problem is set as target in the new World Health Organization’s Neglected Tropical Diseases Roadmap for 2030. Due to a long history of interventions, the Zanzibar islands of Tanzania have reached this goal since 2017. However, challenges occur on the last mile towards interruption of transmission. Our study will investigate new tools and strategies for breaking schistosomiasis transmission.

Methods

The study is designed as an intervention study, documented through repeated cross-sectional surveys (2020–2024). The primary endpoint will be the sensitivity of a surveillance-response approach to detect and react to outbreaks of urogenital schistosomiasis over three years of implementation. The surveys and multi-disciplinary interventions will be implemented in 20 communities in the north of Pemba island. In low-prevalence areas, surveillance-response will consist of active, passive and reactive case detection, treatment of positive individuals, and focal snail control. In hotspot areas, mass drug administration, snail control and behaviour change interventions will be implemented. Parasitological cross-sectional surveys in 20 communities and their main primary schools will serve to adapt the intervention approach annually and to monitor the performance of the surveillance-response approach and impact of interventions. Schistosoma haematobium infections will be diagnosed using reagent strips and urine filtration microscopy, and by exploring novel point-of-care diagnostic tests.

Discussion

Our study will shed light on the field applicability and performance of novel adaptive intervention strategies, and standard and new diagnostic tools for schistosomiasis elimination. The evidence and experiences generated by micro-mapping of S. haematobium infections at community level, micro-targeting of new adaptive intervention approaches, and application of novel diagnostic tools can guide future strategic plans for schistosomiasis elimination in Zanzibar and inform other countries aiming for interruption of transmission.

Trial registration ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493

A spatial hierarchical model for integrating and bias-correcting data from passive and active disease surveillance systems

Disease surveillance data are important for monitoring disease burden and occurrence, and for informing a wide range of efforts to improve population health. Surveillance for infectious diseases may be conducted passively, relying on reports from healthcare facilities, or actively, involving surveys of the population at risk. Passive surveillance typically provides wide spatial coverage, but is subject to biases arising from differences in care-seeking behavior, diagnostic practices, and under-reporting. Active surveillance minimizes these biases, but is typically constrained to small areas and subpopulations due to resource limitations. Methods based on linkage of individual records between passive and active surveillance datasets provide a means to estimate and correct for the biases of each system, leveraging the size and coverage of passive surveillance and the quality of data in active surveillance. We develop a spatial Bayesian hierarchical model for bias-correcting data from both systems to yield an improved estimate of disease measures after adjusting for under-ascertainment. We apply the framework to data from a passive and an active surveillance system for pulmonary tuberculosis (PTB) in Sichuan, China, and estimate the average sensitivity of the active surveillance system at 70% (95% credible interval: 62%, 78%), and the passive system at 30% (95% CI: 24%, 35%). Passive surveillance sensitivity exhibited considerable spatial variability, and was positively associated with a site's gross domestic product per capita. Bias-corrected estimates of county-level PTB prevalence in the province in 2010 identified regions in the southeast with the highest PTB burden, yielding different geographic priorities than previous reports.

Core components, concepts and strategies for parasitic and vector-borne disease elimination with a focus on schistosomiasis: A landscape analysis

Efforts to control and eliminate human schistosomiasis have accelerated over the past decade. In a number of endemic countries and settings, interruption of schistosome transmission has been achieved. In others, Schistosoma infections continue to challenge program managers at different levels, from the complexity of the transmission cycle, over limited treatment options and lack of field-friendly accurate diagnostics, to controversy around adequate intervention strategies. We conducted a landscape analysis on parasitic and vector-borne disease elimination approaches with the aim to identify evidence-based strategies, core components and key concepts for achieving and sustaining schistosomiasis control and for progressing elimination efforts towards interruption of transmission in sub-Saharan Africa. A total of 118 relevant publications were identified from Web of Science, Pubmed and the grey literature and reviewed for their content. In addition, we conducted in-depth interviews with 23 epidemiologists, program managers, policymakers, donors and field researchers. Available evidence emphasizes the need for comprehensive, multipronged and long-term strategies consisting of multiple complementary interventions that must be sustained over time by political commitment and adequate funding in order to reach interruption of transmission. Based on the findings of this landscape analysis, we propose a comprehensive set of intervention strategies for schistosomiasis control and elimination. Before deployment, the proposed interventions will require review, evaluation and validation in the frame of an expert consultation as a step towards adaptation to specific contexts, conditions and settings. Field testing to ensure local relevance and effectiveness is paramount given the diversity of socio-ecological and epidemiological contexts.

This landscape analysis explored successful concepts, approaches and interventions of past and ongoing parasitic and vector-borne disease elimination efforts and programs with regard to relevance for progress in the elimination of human schistosome infections. Schistosomiasis is a disabling, water borne parasitic disease of public health concern with an estimated 250 million people infected worldwide. The long-term morbidity of this neglected tropical disease significantly impacts growth, cognition and socioeconomic development at all ages. Despite increased global efforts to control morbidity and advance elimination, challenges in view of the complex life cycle which involves freshwater sources, intermediate snail hosts and humans, remain. This calls for targeted interventions and concerted programs. According to the evidence from the literature and as proposed by a wide range of key informants, comprehensive, multipronged and long-term strategies supported by strong political commitment and adequate funding are required in order to achieve and sustain the set goals. Based on the findings, we propose here a comprehensive set of intervention strategies for schistosomiasis control and elimination for review and evaluation to inform implementation research needs and elimination program design.

Prenatal and early-life exposure to the Great Chinese Famine increased the risk of tuberculosis in adulthood across two generations

Global food security is a major driver of population health, and food system collapse may have complex and long-lasting effects on health outcomes. We examined the effect of prenatal exposure to the Great Chinese Famine (1958-1962)-the largest famine in human history-on pulmonary tuberculosis (PTB) across consecutive generations in a major center of ongoing transmission in China. We analyzed >1 million PTB cases diagnosed between 2005 and 2018 in Sichuan Province using age-period-cohort analysis and mixed-effects metaregression to estimate the effect of the famine on PTB risk in the directly affected birth cohort (F1) and their likely offspring (F2). The analysis was repeated on certain sexually transmitted and blood-borne infections (STBBI) to explore potential mechanisms of the intergenerational effects. A substantial burden of active PTB in the exposed F1 cohort and their offspring was attributable to the Great Chinese Famine, with more than 12,000 famine-attributable active PTB cases (>1.23% of all cases reported between 2005 and 2018). An interquartile range increase in famine intensity resulted in a 6.53% (95% confidence interval [CI]: 1.19-12.14%) increase in the ratio of observed to expected incidence rate (incidence rate ratio, IRR) in the absence of famine in F1, and an 8.32% (95% CI: 0.59-16.6%) increase in F2 IRR. Increased risk of STBBI was also observed in F2. Prenatal and early-life exposure to malnutrition may increase the risk of active PTB in the exposed generation and their offspring, with the intergenerational effect potentially due to both within-household transmission and increases in host susceptibility.

Current Status of Schistosomiasis Control and Prospects for Elimination in the Dongting Lake Region of the People's Republic of China

Schistosomiasis japonica is an ancient parasitic disease that has severely impacted human health causing a substantial disease burden not only to the Chinese people but also residents of other countries such as the Philippines, Indonesia and, before the 1970s, Japan. Since the founding of the new People's Republic of China (P. R. China), effective control strategies have been implemented with the result that the prevalence of schistosomiasis japonica has decreased markedly in the past 70 years. Historically, the Dongting Lake region in Hunan province is recognised as one of the most highly endemic for schistosomiasis in the P.R. China. The area is characterized by vast marshlands outside the lake embankments and, until recently, the presence of large numbers of domestic animals such as bovines, goats and sheep that can act as reservoir hosts for Schistosoma japonicum. Considerable social, economic and environmental changes have expanded the Oncomelania hupensis hupensis intermediate snail host areas in the Dongting lake region increasing the potential for both the emergence of new hot spots for schistosomiasis transmission, and for its re-emergence in areas where infection is currently under control. In this paper, we review the history, the current endemic status of schistosomiasis and the control strategies in operation in the Dongting Lake region. We also explore epidemiological factors contributing to S. japonicum transmission and highlight key research findings from studies undertaken on schistosomiasis mainly in Hunan but also other endemic Chinese provinces over the past 10 years. We also consider the implications of these research findings on current and future approaches that can lead to the sustainable integrated control and final elimination of schistosomiasis from the P. R. China and other countries in the region where this unyielding disease persists.

The prevalence of noma in northwest Nigeria

Background

Noma, a rapidly progressing infection of the oral cavity, mainly affects children. The true burden is unknown. This study reports estimated noma prevalence in children in northwest Nigeria.

Methods

Oral screening was performed on all ≤15 year olds, with caretaker consent, in selected households during this cross-sectional survey. Noma stages were classified using WHO criteria and caretakers answered survey questions. The prevalence of noma was estimated stratified by age group (0–5 and 6–15 years). Factors associated with noma were estimated using logistic regression.

Results

A total of 177 clusters, 3499 households and 7122 children were included. In this sample, 4239 (59.8%) were 0–5 years and 3692 (52.1%) were female. Simple gingivitis was identified in 3.1% (n=181; 95% CI 2.6 to 3.8), acute necrotising gingivitis in 0.1% (n=10; CI 0.1 to 0.3) and oedema in 0.05% (n=3; CI 0.02 to 0.2). No cases of late-stage noma were detected. Multivariable analysis in the group aged 0–5 years showed having a well as the drinking water source (adjusted odds ratio (aOR) 2.1; CI 1.2 to 3.6) and being aged 3–5 years (aOR 3.9; CI 2.1 to 7.8) was associated with being a noma case. In 6–15 year olds, being male (aOR 1.5; CI 1.0 to 2.2) was associated with being a noma case and preparing pap once or more per week (aOR 0.4; CI 0.2 to 0.8) was associated with not having noma. We estimated that 129120 (CI 105294 to 1 52 947) individuals <15 years of age would have any stage of noma at the time of the survey within the two states. Most of these cases (93%; n=120 082) would be children with simple gingivitis.

Conclusions

Our study identified a high prevalence of children at risk of developing advanced noma. This disease is important but neglected and therefore merits inclusion in the WHO neglected tropical diseases list.

Currently Available Monitoring and Surveillance Systems for Taenia spp., Echinococcus spp., Schistosoma spp., and Soil-Transmitted Helminths at the Control/Elimination Stage: A Systematic Review

An increasing global focus on neglected tropical diseases (NTDs) has resulted in the set up of numerous control and elimination activities worldwide. This is partly true for Taenia solium taeniasis/cysticercosis, the most important foodborne parasitic infection. Despite substantial progress, adequate monitoring and surveillance (M&S) are required to sustain a status of control/elimination. This is often lacking, especially for T. solium. Therefore, the objective was to conduct a systematic literature review of the currently available M&S systems at the control/elimination stage of the four top-ranked helminth NTDs. Specifically, Taenia spp., Echinococcus spp., Schistosoma spp., and soil-transmitted helminths (STHs) were considered to determine if there are any similarities between their M&S systems and whether certain approaches can be adopted from each other. The systematic review demonstrated that rigorous M&S systems have been designed for the control/elimination stage of both STHs and schistosomiasis, particularly in China. On the other hand, a concept of M&S for Taenia spp. and Echinococcus spp. has not been fully developed yet, due to a lack of epidemiological data and the fact that many endemic countries are far away from reaching control/elimination. Moreover, accurate diagnostic tools for all four diseases are still imperfect, which complicates proper M&S. Finally, there is an urgent need to develop and harmonize/standardize M&S activities in order to reliably determine and compare the epidemiological situation worldwide.

Hydroclimatic drivers of highly seasonal leptospirosis incidence suggest prominent soil reservoir of pathogenic Leptospira spp. in rural western China

Climate exerts complex influences on leptospirosis transmission, affecting human behavior, zoonotic host population dynamics, and survival of the pathogen in the environment. Here, we describe the spatiotemporal distribution of leptospirosis incidence reported to China’s National Infectious Disease Surveillance System from 2004–2014 in an endemic region in western China, and employ distributed lag models at annual and sub-annual scales to analyze its association with hydroclimatic risk factors and explore evidence for the potential role of a soil reservoir in the transmission of Leptospira spp. More than 97% of the 2,934 reported leptospirosis cases occurred during the harvest season between August and October, and most commonly affected farmers (83%). Using a distributed lag Poisson regression framework, we characterized incidence rate ratios (IRRs) associated with interquartile range increases in precipitation of 3.45 (95% confidence interval 2.57–4.64) over 0-1-year lags, and 1.90 (1.18–3.06) over 0-15-week lags. Adjusting for soil moisture decreased IRRs for precipitation at both timescales (yearly adjusted IRR: 1.05, 0.74–1.49; weekly adjusted IRR: 1.36, 0.72–2.57), suggesting precipitation effects may be mediated through soil moisture. Increased soil moisture was positively associated with leptospirosis at both timescales, suggesting that the survival of pathogenic Leptospira spp. in moist soils may be a critical control on harvest-associated leptospirosis transmission in the study region. These results support the hypothesis that soils may serve as an environmental reservoir and may play a significant yet underrecognized role in leptospirosis transmission.

Leptospirosis is among the leading causes of morbidity from zoonotic infections worldwide, affecting populations that are exposed to contaminated water. The disease is caused by Leptospira spp. bacteria, which are transmitted to humans either through direct contact with infected animals, or indirectly through the environment. Climatic conditions can influence transmission by altering human exposure, animal host population dynamics, and environmental conditions that allow Leptospira spp. to persist in the environment (e.g., moist environments, warm temperatures). Here, we investigated the spatiotemporal distribution of leptospirosis cases in a rural setting in western China and estimated the association between hydroclimatic conditions and leptospirosis incidence. We found that incidence of leptospirosis—especially high amongst farmers—may be associated with rice harvest, and modulated by prior bacterial accumulation within the soil under moist conditions. These results corroborate previous findings that soils may be underrecognized environmental reservoirs of pathogenic Leptospira spp., and that their role in explaining leptospirosis incidence should be considered when developing prevention programs.

Evidence for heterogeneity in China's progress against pulmonary tuberculosis: uneven reductions in a major center of ongoing transmission, 2005-2017

Background

China contributed 8.9% of all incident cases of tuberculosis globally in 2017, and understanding the spatiotemporal distribution of pulmonary tuberculosis (PTB) in major transmission foci in the country is critical to ongoing efforts to improve population health.

Methods

We estimated annual PTB notification rates and their spatiotemporal distributions in Sichuan province, a major center of ongoing transmission, from 2005 to 2017. Time series decomposition was used to obtain trend components from the monthly incidence rate time series. Spatiotemporal cluster analyses were conducted to detect spatiotemporal clusters of PTB at the county level.

Results

From 2005 to 2017, 976,873 cases of active PTB and 388,739 cases of smear-positive PTB were reported in Sichuan Province, China. During this period, the overall reported incidence rate of active PTB decreased steadily at a rate of decrease (3.77 cases per 100,000 per year, 95% confidence interval (CI): 3.28–4.31) that was slightly faster than the national average rate of decrease (3.14 cases per 100,000 per year, 95% CI: 2.61–3.67). Although reported PTB incidence decreased significantly in most regions of the province, incidence was observed to be increasing in some counties with high HIV incidence and ethnic minority populations. Active and smear-positive PTB case reports exhibited seasonality, peaking in March and April, with apparent links to social dynamics and climatological factors.

Conclusions

While PTB incidence rates decreased strikingly in the study area over the past decade, improvements have not been equally distributed. Additional surveillance and control efforts should be guided by the seasonal-trend and spatiotemporal cluster analyses presented here, focusing on areas with increasing incidence rates, and updated to reflect the latest information from real-time reporting.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4262-2) contains supplementary material, which is available to authorized users.

Contextualizing Schistosoma haematobium transmission in Ghana: Assessment of diagnostic techniques and individual and community water-related risk factors

OBJECTIVES

The study assessed associations between Schistosoma haematobium infection (presence of parasite eggs in urine or hematuria) and self-reported metrics (macrohematuria, fetching surface water, or swimming) to evaluate their performance as proxies of infection in presence of regular preventive chemotherapy. It also examined community water characteristics (safe water access, surface water access, and groundwater quality) to provide context for schistosomiasis transmission in different types of communities and propose interventions.

METHODS

Logistic regression was used to assess the associations between the various measured and self-reported metrics in a sample of 897 primary school children in 30 rural Ghanaian communities. Logistic regression was also used to assess associations between community water characteristics, self-reported water-related behaviors and S. haematobium infection. Communities were subsequently categorized as candidates for three types of interventions: provision of additional safe water sources, provision of groundwater treatment, and health education about water-related disease risk, depending on their water profile.

RESULTS

Microhematuria presence measured with a reagent strip was a good proxy of eggs in urine at individual (Kendall's τ_b = 0.88, p < 0.001) and at school-aggregated (Spearman's r_s = 0.96, p < 0.001) levels. Self-reported macrohematuria and swimming were significantly associated (p < 0.05) with egg presence, but self-reported fetching was not. Of the community water characteristics, greater surface water access and presence of groundwater quality problems were significantly associated with increased likelihood of fetching, swimming, and S. haematobium infection. Access to improved water sources did not exhibit an association with any of these outcomes.

CONCLUSIONS

The study illustrates that in presence of regular school-based treatment with praziquantel, microhematuria assessed via reagent strips remains an adequate proxy for S. haematobium infection in primary schoolchildren. Community water profiles, in combination with self-reported water-related behaviors, can help elucidate reasons for some endemic communities continuing to experience ongoing transmission and tailor interventions to these local contexts to achieve sustainable control.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles

BACKGROUND

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches.

METHODOLOGY

Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables.

PRINCIPAL FINDINGS

Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables.

CONCLUSIONS/SIGNIFICANCE

The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance on surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

Neglected tropical diseases: exploring long term practical approaches to achieve sustainable disease elimination and beyond

Background

Remarkable progress has been made in the fight against neglected tropical diseases, but new challenges have emerged. Innovative diagnostics, better drugs and new insecticides are often identified as the priority; however, access to these new tools may not be sufficient to achieve and sustain disease elimination, if certain challenges and priorities are not considered.

Main body

The authors summarise key operational challenges, and based on these, identify two major priorities: strengthening the capacity of the primary health care health system in correctly diagnosing and managing neglected tropical diseases; and establishing an effective disease surveillance process.

Five steps are proposed as concrete actions to build an effective primary health care service for neglected tropical diseases, and a health management information system capable of accurately reporting these diseases. Community engagement and formalization of community health workers role are proposed as essential components of these steps.

Shift of financial support from disease oriented programmes to disease integrated interventions, improved access to international guidelines for primary health care staff, and availability of donated drugs in health care structures are also suggested as key elements of the proposed process.

Conclusion

The authors conclude that failure to address these priorities now may lead to further challenges on the long path towards neglected tropical disease elimination and beyond.

Electronic supplementary material

The online version of this article (doi: 10.1186/s40249-017-0361-8) contains supplementary material, which is available to authorized users.

Temporal and long-term trend analysis of class C notifiable diseases in China from 2009 to 2014

OBJECTIVES

Time series models are effective tools for disease forecasting. This study aims to explore the time series behaviour of 11 notifiable diseases in China and to predict their incidence through effective models.

SETTINGS AND PARTICIPANTS

The Chinese Ministry of Health started to publish class C notifiable diseases in 2009. The monthly reported case time series of 11 infectious diseases from the surveillance system between 2009 and 2014 was collected.

METHODS

We performed a descriptive and a time series study using the surveillance data. Decomposition methods were used to explore (1) their seasonality expressed in the form of seasonal indices and (2) their long-term trend in the form of a linear regression model. Autoregressive integrated moving average (ARIMA) models have been established for each disease.

RESULTS

The number of cases and deaths caused by hand, foot and mouth disease ranks number 1 among the detected diseases. It occurred most often in May and July and increased, on average, by 0.14126/100 000 per month. The remaining incidence models show good fit except the influenza and hydatid disease models. Both the hydatid disease and influenza series become white noise after differencing, so no available ARIMA model can be fitted for these two diseases.

CONCLUSION

Time series analysis of effective surveillance time series is useful for better understanding the occurrence of the 11 types of infectious disease.

Detecting genotyping errors at Schistosoma japonicum microsatellites with pedigree information

BACKGROUND

Schistosomiasis japonica remains a major public health problem in China. Integrating molecular analyses, such as population genetic analyses, of the parasite into the on-going surveillance programs is helpful in exploring the factors causing the persistence and/or spread of Schistosoma japonicum. However, genotyping errors can seriously affect the results of such studies, unless accounted for in the analyses.

METHODS

We assessed the genotyping errors (missing alleles or false alleles) of seven S. japonicum microsatellites, using a pedigree data approach for schistosome miracidia, which were stored on Whatman FTA cards.

RESULTS

Among 107 schistosome miracidia successfully genotyped, resulting in a total of 715 loci calls, a total of 31 genotyping errors were observed with 25.2% of the miracidia having at least one error. The error rate per locus differed among loci, which ranged from 0 to 9.8%, with the mean error rate 4.3% over loci. With the parentage analysis software Cervus, the assignment power with these seven markers was estimated to be 89.5% for one parent and 99.9% for a parent pair. One locus was inferred to have a high number of null alleles and a second with a high mistyping rate.

CONCLUSION

To the authors' knowledge, this is the first time that S. japonicum pedigrees have been used in an assessment of genotyping errors of microsatellite markers. The observed locus-specific error rate will benefit downstream epidemiological or ecological analyses of S. japonicum with the markers.