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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: The Bangladesh Lymphatic Filariasis (LF) Elimination Programme has made significant progress in interrupting transmission through mass drug administration (MDA) and has now focussed its efforts on scaling up managing morbidity and preventing disability (MMDP) activities to deliver the minimum package of care to people affected by LF clinical conditions. This paper highlights the Bangladesh LF Programme’s success in conducting a large-scale cross-sectional survey to determine the number of people affected by lymphoedema and hydrocoele, which enabled clinical risk maps to be developed for targeted interventions across the 34 endemic districts (19 high endemic; 15 low endemic). Methodology/Principal findings: In the 19 high endemic districts, 8,145 community clinic staff were trained to identify and report patients in their catchment area. In the 15 low endemic districts, a team of 10 trained field assistants conducted active case finding with cases reported via a SMS mHealth tool. Disease burden and prevalence maps were developed, with morbidity hotspots identified at sub-district level based on a combination of the highest prevalence rates per 100,000 and case-density rates per square kilometre (km2). The relationship between morbidity and baseline microfilaria (mf) prevalence was also examined. In total 43,678 cases were identified in the 19 high endemic districts; 30,616 limb lymphoedema (70.1%; female 55.3%), 12,824 hydrocoele (29.4%), and 238 breast/female genital swelling (0.5%). Rangpur Division reported the highest cases numbers and prevalence of lymphoedema (26,781 cases, 195 per 100,000) and hydrocoele (11661 cases, 169.6 per 100,000), with lymphoedema predominately affecting females (n = 21,652). Rangpur and Lalmonirhat Districts reported the highest case numbers (n = 11,199), and prevalence (569 per 100,000) respectively, with five overlapping lymphoedema and hydrocoele sub-district hotspots. In the 15 low endemic districts, 732 cases were identified; 661 lymphoedema (90.2%; female 39.6%), 56 hydrocoele (7.8%), and 15 both conditions (2.0%). Spearman’s correlation analysis found morbidity and mf prevalence significantly positively correlated (r = 0.904; p<0.01). Conclusions/Significance: The Bangladesh LF Programme has developed one of the largest, most comprehensive country databases on LF clinical conditions in the world. It provides an essential database for health workers to identify local morbidity hotspots, deliver the minimum package of care, and address the dossier elimination requirements. [ABSTRACT FROM AUTHOR]

Background: Asymptomatic Leishmania donovani infections outnumber clinical presentations, however the predictors for development of active disease are not well known. We aimed to identify serological, immunological and genetic markers for progression from L. donovani infection to clinical Visceral Leishmaniasis (VL). Methods: We enrolled all residents >2 years of age in 27 VL endemic villages in Bihar (India). Blood samples collected on filter paper on two occasions 6–12 months apart, were tested for antibodies against L. donovani with rK39-ELISA and DAT. Sero converters, (negative for both tests in the first round but positive on either of the two during the second round) and controls (negative on both tests on both occasions) were followed for three years. At the start of follow-up venous blood was collected for the following tests: DAT, rK39- ELISA, Quantiferon assay, SNP/HLA genotyping and L.donovani specific quantitative PCR. Results: Among 1,606 subjects enrolled,17 (8/476 seroconverters and 9/1,130 controls) developed VL (OR 3.1; 95% CI 1.1–8.3). High DAT and rK39 ELISA antibody titers as well as positive qPCR were strongly and significantly associated with progression from seroconversion to VL with odds ratios of 19.1, 30.3 and 20.9 respectively. Most VL cases arose early (median 5 months) during follow-up. Conclusion: We confirmed the strong association between high DAT and/or rK39 titers and progression to disease among asymptomatic subjects and identified qPCR as an additional predictor. Low predictive values do not warrant prophylactic treatment but as most progressed to VL early during follow-up, careful oberservation of these subjects for at least 6 months is indicated. [ABSTRACT FROM AUTHOR]