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Background: Although trachoma causes more cases of preventable blindness than any other infectious disease, a combination of strategies is reducing its global prevalence. As a district moves toward eliminating trachoma as a public health problem, national programs conduct trachoma impact surveys (TIS) to assess whether to stop preventative interventions and trachoma surveillance surveys (TSS) to determine whether the prevalence of active trachoma has rebounded after interventions have halted. In some contexts, programs also conduct trachomatous trichiasis (TT)-only surveys. A few costing studies of trachoma prevalence surveys exist, but none examine TIS, TSS, or TT-only surveys. Methodology/Principal findings: We assessed the incremental financial cost to the national program of TIS, TSS, and TT-only surveys, which are standardized cluster-sampled prevalence surveys. We conducted a retrospective review of expenditures and grant disbursements for TIS and TSS in 322 evaluation units in 11 countries between 2011 and 2018. We also assessed the costs of three pilot and five standard TT-only surveys in four countries between 2017 and 2018. The median cost of TIS and TSS was $8,298 per evaluation unit [interquartile range (IQR): $6,532–$10,111, 2017 USD]. Based on a linear regression with bootstrapped confidence intervals, after controlling for country, costs per survey did not change significantly over time but did decline by $83 per survey implemented in a single round (95% CI: -$108 –-$63). Of total costs, 80% went to survey fieldwork; of that, 58% went towards per diems and 38% towards travel. TT-only surveys cost a median of $9,707 (IQR: $8,537–$11,635); within a given country, they cost slightly more (106% [IQR: 94%–136%]) than TIS and TSS. Conclusions/Significance: The World Health Organization requires trachoma prevalence estimates for validating the elimination of trachoma as a public health problem. This study will help programs improve their planning as they assemble resources for that effort. [ABSTRACT FROM AUTHOR]

Targeted environmental and ecosystem management remain crucial in control of dengue. However, providing detailed environmental information on a large scale to effectively target dengue control efforts remains a challenge. An important piece of such information is the extent of the presence of potential dengue vector breeding sites, which consist primarily of open containers such as ceramic jars, buckets, old tires, and flowerpots. In this paper we present the design and implementation of a pipeline to detect outdoor open containers which constitute potential dengue vector breeding sites from geotagged images and to create highly detailed container density maps at unprecedented scale. We implement the approach using Google Street View images which have the advantage of broad coverage and of often being two to three years old which allows correlation analyses of container counts against historical data from manual surveys. Containers comprising eight of the most common breeding sites are detected in the images using convolutional neural network transfer learning. Over a test set of images the object recognition algorithm has an accuracy of 0.91 in terms of F-score. Container density counts are generated and displayed on a decision support dashboard. Analyses of the approach are carried out over three provinces in Thailand. The container counts obtained agree well with container counts from available manual surveys. Multi-variate linear regression relating densities of the eight container types to larval survey data shows good prediction of larval index values with an R-squared of 0.674. To delineate conditions under which the container density counts are indicative of larval counts, a number of factors affecting correlation with larval survey data are analyzed. We conclude that creation of container density maps from geotagged images is a promising approach to providing detailed risk maps at large scale. [ABSTRACT FROM AUTHOR]

Background: Mathematical models are increasingly being used to evaluate strategies aiming to achieve the control or elimination of parasitic diseases. Recently, owing to growing realization that process-oriented models are useful for ecological forecasts only if the biological processes are well defined, attention has focused on data assimilation as a means to improve the predictive performance of these models. Methodology and principal findings: We report on the development of an analytical framework to quantify the relative values of various longitudinal infection surveillance data collected in field sites undergoing mass drug administrations (MDAs) for calibrating three lymphatic filariasis (LF) models (EPIFIL, LYMFASIM, and TRANSFIL), and for improving their predictions of the required durations of drug interventions to achieve parasite elimination in endemic populations. The relative information contribution of site-specific data collected at the time points proposed by the WHO monitoring framework was evaluated using model-data updating procedures, and via calculations of the Shannon information index and weighted variances from the probability distributions of the estimated timelines to parasite extinction made by each model. Results show that data-informed models provided more precise forecasts of elimination timelines in each site compared to model-only simulations. Data streams that included year 5 post-MDA microfilariae (mf) survey data, however, reduced each model’s uncertainty most compared to data streams containing only baseline and/or post-MDA 3 or longer-term mf survey data irrespective of MDA coverage, suggesting that data up to this monitoring point may be optimal for informing the present LF models. We show that the improvements observed in the predictive performance of the best data-informed models may be a function of temporal changes in inter-parameter interactions. Such best data-informed models may also produce more accurate predictions of the durations of drug interventions required to achieve parasite elimination. Significance: Knowledge of relative information contributions of model only versus data-informed models is valuable for improving the usefulness of LF model predictions in management decision making, learning system dynamics, and for supporting the design of parasite monitoring programmes. The present results further pinpoint the crucial need for longitudinal infection surveillance data for enhancing the precision and accuracy of model predictions of the intervention durations required to achieve parasite elimination in an endemic location. [ABSTRACT FROM AUTHOR]

Genome wide association studies (GWASs) have revealed multiple genetic variants associated with leprosy in the Chinese population. The aim of our study was to utilize the genetic variants to construct a risk prediction model through a weighted genetic risk score (GRS) in a Chinese set and to further assess the performance of the model in identifying higher-risk contact individuals in an independent set. The highest prediction accuracy, with an area under the curve (AUC) of 0.743 (95% confidence interval (CI): 0.729–0.757), was achieved with a GRS encompassing 25 GWAS variants in a discovery set that included 2,144 people affected by leprosy and 2,671 controls. Individuals in the high-risk group, based on genetic factors (GRS > 28.06), have a 24.65 higher odds ratio (OR) for developing leprosy relative to those in the low-risk group (GRS≤18.17). The model was then applied to a validation set consisting of 1,385 people affected by leprosy and 7,541 individuals in contact with leprosy, which yielded a discriminatory ability with an AUC of 0.707 (95% CI: 0.691–0.723). When a GRS cut-off value of 22.38 was selected with the optimal sensitivity and specificity, it was found that 39.31% of high risk contact individuals should be screened in order to detect leprosy in 64.9% of those people affected by leprosy. In summary, we developed and validated a risk model for the prediction of leprosy that showed good discrimination capabilities, which may help physicians in the identification of patients coming into contact with leprosy and are at a higher-risk of developing this condition. [ABSTRACT FROM AUTHOR]

Background: Buruli ulcer (BU) is a chronic necrotizing infectious skin disease caused by Mycobacterium ulcerans. The treatment with BU-specific antibiotics is initiated after clinical suspicion based on the WHO clinical and epidemiological criteria. This study aimed to estimate the predictive values of these criteria and how they could be improved. Methodology/Principal findings: A total of 224 consecutive patients presenting with skin and soft tissue lesions that could be compatible with BU, including those recognized as unlikely BU by experienced clinicians, were recruited in two BU treatment centers in southern Benin between March 2012 and March 2015. For every participant, the WHO and four additional epidemiological and clinical diagnostic criteria were recorded. For microbiological confirmation, direct smear examination and IS2404 PCR were performed. We fitted a logistic regression model with PCR positivity for BU confirmation as outcome variable. On univariate analysis, most of the clinical and epidemiological WHO criteria were associated with a positive PCR result. However, lesions on the lower limbs and WHO category 3 lesions were rather associated with a negative PCR result (respectively OR: 0.4, 95%CI: 0.3–0.8; OR: 0.5, 95%IC: 0.3–0.9). Among the additional characteristics studied, the characteristic smell of BU was strongest associated with a positive PCR result (OR = 16.4; 95%CI = 7.5–35.6). Conclusion/Significance: The WHO diagnostic criteria could be improved upon by differentiating between lesions on the upper and lower limbs and by including lesion size and the characteristic smell recognized by experienced clinicians. [ABSTRACT FROM AUTHOR]

Introduction: Brucellosis and leptospirosis are among neglected tropical zoonotic diseases particularly in the resource limited countries. Despite being endemic in these countries, there is paucity of information on its magnitude. This study investigated seropositivity of Brucella spp. and Leptospira spp., and associated factors among abattoir workers and meat vendors in the city of Mwanza, Tanzania. Methodology: A community based cross-sectional study was conducted in Mwanza city from May to July 2017. Socio-demographic and other relevant information were collected. Detection of Brucella spp. and Leptospira spp. antibodies were done using slide agglutination test and microscopic agglutination test, respectively. Data were analyzed using STATA version 13 Software. Findings: A total of 250 participants (146 abattoir workers and 104 meat vendors) were enrolled with median age of 31 (IQR: 25–38) years. The overall, seropositivity of Brucella spp. antibodies was 48.4% (95% Cl: 42–54). Seropositivity of B. abortus was significantly higher than that of B. melitensis (46.0%, 95%Cl: 39–52 vs. 23.6%, 95% Cl: 18–28, P<0.001) while seropositivity of both species was 21.2% (95%Cl: 16–26). The seropositivity of Leptospira spp. was 10.0% (95% CI: 6–13) with predominance of Leptospira kirschneri serovar Sokoine which was detected in 7.2% of the participants. Being abattoir worker (OR: 2.19, 95% CI 1.06–4.54, p = 0.035) and long work duration (OR: 1.06, 95%CI: 1.01–1.11, p = 0.014) predicted presence of both B.abortus and B. melitensis antibodies. Only being married (p = 0.041) was significantly associated with seropositivity of Leptospira spp. Primary education was the only factor independently predicted presence of Brucella spp. antibodies among abattoir workers on sub-analysis of occupational exposure. None of factors were found to be associated with presence of Brucella spp. antibodies among meat vendors on sub-analysis. Conclusion: Seropositivity of B.abortus antibodies among abattoir workers and meat vendors is high and seem to be a function of being abattoir worker, having worked for long duration in the abattoir and having primary education. In addition, a significant proportion of abattoir workers and meat vendors in the city was seropositive for Leptospira kirschneri serovar Sokoine. There is a need to consider ‘one health approach’ in devising appropriate strategies to control these diseases in the developing countries. [ABSTRACT FROM AUTHOR]

Background: Evidence from recent studies assessing the impact of school water, sanitation and hygiene (WASH) interventions on child health has been mixed. Self-reports of disease are subject to bias, and few WASH impact evaluations employ objective health measures to assess reductions in disease and exposure to pathogens. We utilized antibody responses from dried blood spots (DBS) to measure the impact of a school WASH intervention on infectious disease among pupils in Mali. Methodology/Principal findings: We randomly selected 21 beneficiary primary schools and their 21 matched comparison schools participating in a matched-control trial of a comprehensive school-based WASH intervention in Mali. DBS were collected from 20 randomly selected pupils in each school (n = 807). We analyzed eluted IgG from the DBS using a Luminex multiplex bead assay to 28 antigens from 17 different pathogens. Factor analysis identified three distinct latent variables representing vector-transmitted disease (driven primarily by dengue), food/water-transmitted enteric disease (driven primarily by Escherichia coli and Vibrio cholerae), and person-to-person transmitted enteric disease (driven primarily by norovirus). Data were analyzed using a linear latent variable model. Antibody evidence of food/water-transmitted enteric disease (change in latent variable mean (β) = -0.24; 95% CI: -0.53, -0.13) and person-to-person transmitted enteric disease (β = -0.17; 95% CI: -0.42, -0.04) was lower among pupils attending beneficiary schools. There was no difference in antibody evidence of vector-transmitted disease (β = 0.11; 95% CI: -0.05, 0.33). Conclusions/Significance: Evidence of enteric disease was lower among pupils attending schools benefitting from school WASH improvements than students attending comparison schools. These findings support results from the parent study, which also found reduced incidence of self-reported diarrhea among pupils of beneficiary schools. DBS collection was feasible in this resource-poor field setting and provided objective evidence of disease at a low cost per antigen analyzed, making it an effective measurement tool for the WASH field. Trial registration: The trial was registered at ClinicalTrials.gov () [ABSTRACT FROM AUTHOR]

Internet-based surveillance methods for vector-borne diseases (VBDs) using “big data” sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such “digital disease detection” methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of “digital epidemiology.” We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD. [ABSTRACT FROM AUTHOR]

Background: Tungiasis is a neglected tropical disease caused by female sand fleas (Tunga penetrans) embedded in the skin. The disease is associated with important morbidity. Tungiasis is endemic along the Coast of Kenya with a prevalence ranging from 11% to 50% in school-age children. Hitherto, studies on epidemiological characteristics of tungiasis in Africa are scanty. Methods: In a cross-sectional study 1,086 individuals from 233 households in eight villages located in Kakuyuni and Malanga Sub-locations, Kilifi County, on the Kenyan Coast, were investigated. Study participants were examined systematically and the presence and severity of tungiasis were determined using standard methods. Demographic, socio-economic, environmental and behavioral risk factors of tungiasis were assessed using a structured questionnaire. Data were analyzed using bivariate and multivariate regression analysis. Results: The overall prevalence of tungiasis was 25.0% (95% CI 22.4–27.5%). Age-specific prevalence followed an S-shaped curve, peaking in the under-15 year old group. In 42.5% of the households at least one individual had tungiasis. 15.1% of patients were severely infected (≥ 30 lesions). In the bivariate analysis no specific animal species was identified as a risk factor for tungiasis. Multivariate analysis showed that the occurrence of tungiasis was related to living in a house with poor construction characteristics, such as mud walls (OR 3.35; 95% CI 1.71–6.58), sleeping directly on the floor (OR 1.68; 95% CI 1.03–2.74), the number of people per sleeping room (OR = 1.77; 95% CI 1.07–2.93) and washing the body without soap (OR = 7.36; 95% CI 3.08–17.62). The odds of having severe tungiasis were high in males (OR 2.29; 95% CI 1.18–44.6) and were very high when only mud puddles were available as a water source and lack of water permitted washing only once a day (OR 25.48 (95% CI 3.50–185.67) and OR 2.23 (95% CI 1.11–4.51), respectively). Conclusions: The results of this study show that in rural Kenya characteristics of poverty determine the occurrence and the severity of tungiasis. Intra-domiciliary transmission seems to occur regularly. [ABSTRACT FROM AUTHOR]

Background: Infectious diseases are a leading threat to public health. Accurate and timely monitoring of disease risk and progress can reduce their impact. Mentioning a disease in social networks is correlated with physician visits by patients, and can be used to estimate disease activity. Dengue is the fastest growing mosquito-borne viral disease, with an estimated annual incidence of 390 million infections, of which 96 million manifest clinically. Dengue burden is likely to increase in the future owing to trends toward increased urbanization, scarce water supplies and, possibly, environmental change. The epidemiological dynamic of Dengue is complex and difficult to predict, partly due to costly and slow surveillance systems. Methodology / Principal findings: In this study, we aimed to quantitatively assess the usefulness of data acquired by Twitter for the early detection and monitoring of Dengue epidemics, both at country and city level at a weekly basis. Here, we evaluated and demonstrated the potential of tweets modeling for Dengue estimation and forecast, in comparison with other available web-based data, Google Trends and Wikipedia access logs. Also, we studied the factors that might influence the goodness-of-fit of the model. We built a simple model based on tweets that was able to ‘nowcast’, i.e. estimate disease numbers in the same week, but also ‘forecast’ disease in future weeks. At the country level, tweets are strongly associated with Dengue cases, and can estimate present and future Dengue cases until 8 weeks in advance. At city level, tweets are also useful for estimating Dengue activity. Our model can be applied successfully to small and less developed cities, suggesting a robust construction, even though it may be influenced by the incidence of the disease, the activity of Twitter locally, and social factors, including human development index and internet access. Conclusions: Tweets association with Dengue cases is valuable to assist traditional Dengue surveillance at real-time and low-cost. Tweets are able to successfully nowcast, i.e. estimate Dengue in the present week, but also forecast, i.e. predict Dengue at until 8 weeks in the future, both at country and city level with high estimation capacity. [ABSTRACT FROM AUTHOR]

Background: Prevention is most effective in reducing dengue infection risk, especially in endemic countries like Pakistan. Evaluation of public awareness and health beliefs regarding dengue fever (DF) is important for devising disease control strategies. This study assessed dengue knowledge, health beliefs, and preventive practices against DF in different socioeconomic groups of Karachi, Pakistan. Methodology: In this community-based cross-sectional study, 6 randomly selected towns were visited, 2 persons (man and woman) per household were interviewed using a structured questionnaire, and household practices were observed. Information regarding DF was shared through a printed pamphlet. Multivariate logistic regression analysis of variables associated with dengue knowledge and practices was conducted. Principal Findings: We interviewed 608 Karachi residents (mean age: 33.2 ± 13.35 years); 7.7%, 71.9%, and 20.4% had a high, middle, and low socioeconomic status, respectively. The mean knowledge score was 6.4 ± 2.10 out of 14. The mean preventive practices score was 9 ± 1.8 out of 17. Predictors of dengue knowledge were perceived threat (odds ratio [OR] = 1.802; 95% confidence interval [CI] = 1.19–2.71; p = 0.005), self-efficacy (OR = 2.910; 95% CI = 1.77–4.76; p = 0.000), and television as an information source (OR = 3.202; 95% CI = 1.97–5.17; p = 0.000). Predictors of dengue preventive practices were perceived threat (OR = 1.502; 95% CI = 1.02–2.19; p = 0.036), self-efficacy (OR = 1.982; 95% CI = 1.34–2.91; p = 0.000), and dengue knowledge (OR = 1.581; 95% CI = 1.05–2.37; p = 0.028). Conclusions: Public knowledge about DF is low in Karachi. Knowledge, threat perception, and self-efficacy are significant predictors of adequate dengue preventive practices. Prevention and control strategies should focus on raising awareness about dengue contraction risk and severity through television. Health messages should be designed to increase individual self-efficacy. [ABSTRACT FROM AUTHOR]

Background: Trachomatous trichiasis significantly reduces vision and health related quality of life (QoL). Although trichiasis surgery is widely performed to treat trichiasis, there is little data on the effect of surgery on QoL. We measured the impact of trichiasis surgery on vision and health related QoL in a longitudinal study from Amhara Region, Ethiopia. Methodology/Principal Findings: We recruited 1000 adult participants with trichiasis (cases) and 200 comparison participants, matched to every fifth trichiasis case on age (+/- two years), sex and location. Vision-related quality of life (VRQoL) and health-related quality of life (HRQoL) were measured using the WHO/PBD-VF20 and WHOQOL-BREF questionnaires respectively, at enrolment and 12 months after enrolment. All trichiasis cases received free standard trichiasis surgery immediately after enrolment. The mean difference in QoL scores between enrolment and follow-up for cases and comparison participants, and the difference-in-differences by baseline trichiasis status was analysed using random effects linear regression, the later adjusted for age, sex and socioeconomic status. At 12-months follow-up, data was collected from 980 (98%) and 198 (98%) trichiasis cases and comparison participants respectively. At this follow-up visit, VRQoL and HRQoL scores of trichiasis cases improved substantially in all subscales and domains by 19.1–42.0 points (p<0.0001) and 4.7–17.2 points (p<0.0001), respectively. In contrast, among the comparison participants, there was no evidence of improvement in VRQoL and HRQoL domain scores during follow-up. The improvement in VRQoL and HRQoL in cases was independent of the presence of visual acuity improvement at 12 months. Conclusions/Significance: Trichiasis surgery substantially improves both VRQoL and HRQoL regardless of visual acuity change. Unprecedented effort is needed to scale-up trichiasis surgical programmes not only to prevent the risk of sight loss but also to improve overall wellbeing and health perception of affected individuals. [ABSTRACT FROM AUTHOR]

Background: Access to laboratory diagnosis can be a challenge for individuals suspected of Buruli Ulcer (BU). Our objective was to develop a clinical score to assist clinicians working in resource-limited settings for BU diagnosis. Methododology/Principal Findings: Between 2011 and 2013, individuals presenting at Akonolinga District Hospital, Cameroon, were enrolled consecutively. Clinical data were collected prospectively. Based on a latent class model using laboratory test results (ZN, PCR, culture), patients were categorized into high, or low BU likelihood. Variables associated with a high BU likelihood in a multivariate logistic model were included in the Buruli score. Score cut-offs were chosen based on calculated predictive values. Of 325 patients with an ulcerative lesion, 51 (15.7%) had a high BU likelihood. The variables identified for the Buruli score were: characteristic smell (+3 points), yellow color (+2), female gender (+2), undermining (+1), green color (+1), lesion hyposensitivity (+1), pain at rest (-1), size >5cm (-1), locoregional adenopathy (-2), age above 20 up to 40 years (-3), or above 40 (-5). This score had AUC of 0.86 (95%CI 0.82–0.89), indicating good discrimination between infected and non-infected individuals. The cut-off to reasonably exclude BU was set at scores <0 (NPV 96.5%; 95%CI 93.0–98.6). The treatment threshold was set at a cut-off ≥4 (PPV 69.0%; 95%CI 49.2–84.7). Patients with intermediate BU probability needed to be tested by PCR. Conclusions/Significance: We developed a decisional algorithm based on a clinical score assessing BU probability. The Buruli score still requires further validation before it can be recommended for wide use. [ABSTRACT FROM AUTHOR]

The article offers information on the guidelines development group meeting conducted by World Health Organization (WHO)'s Control of Neglected Tropical Diseases department for the control of soil-transmitted helminths in high-risk groups. Topics include meta-analysis on the impact of mass drug administration (MDA) on weight gain of children; decision made by WHO on the basis of health and economic benefits; and weight-for-age distribution between ages three and four.