An outbreak of cholera in Medipally village, Andhra Pradesh, India, 2013

Background: Cholera continues to remain endemic in over 50 countries and has caused large epidemics with around 3\u20135 million cases occurring every year in Asia alone. In India, cholera is endemic in many states. However, etiological information and age-specific incidence related to cholera outbreaks is limited. In November 2013, district authorities reported a cluster of diarrheal disease among residents of Medipally to the state surveillance unit. We investigated this cluster to confirm its etiology, describe its magnitude, identify potential risk factors, and make recommendations for control. Findings: A house-to-house active search was conducted to identify cases of acute diarrhea and collect information on drinking water source. Drinking water samples were collected from common water sources and sampled households to test for bacteriological quality. Ten stool samples were collected for culture. A matched case\u2013control study was conducted to identify the risk factors. A total of 138 case-patients of diarrhea (Attack rate: 11.5/100; Population: 15 1,200) and 1 death (Case Fatality Ratio: 0.72/100) were identified. Five of the 10 stool samples were culture positive for V. cholerae, serogroup O1 El Tor. Drinking water from the overhead tank [Adjusted OR (AOR): 31.94, 95 % CI: 7.3-139.5] was associated with risk of developing illness. Conclusions: This outbreak affected nearly 11% of the village population and was due to contamination of the main drinking water source. Outbreaks such as this can be prevented by constructing the drain away from the water pipelines and by monitoring regular chlorination of drinking water source and inspection of pipelines for damage

Spatial distribution and cluster analysis of dengue using self organizing maps in Andhra Pradesh, India, 2011-2013

Background and objectives Dengue is an emerging and re-emerging infectious disease, transmitted by mosquitoes. It is mostly prevalent in tropical and sub-tropical regions of the world, particularly, in Asia-Pacific region. To understand the epidemiology and spatial distribution of dengue, a retrospective surveillance study was conducted in the state of Andhra Pradesh, India during 2011–2013. Material and methods District-wise disease endemicity levels were mapped through geographical information system (GIS) tools. Spatial statistical analysis such as Getis-Ord Gi* was performed to identify hot spots and cold spots of dengue disease. Similarly self organizing maps (SOM), a datamining tool was also applied to understand the endemicity patterns in study areas. Results The analysis shows that districts of Warangal, Karimnagar, Khammam and Vizianagaram are reported as hot spot regions whereas Adilabad and Nizamabad reported as cold spots for dengue. The SOM classify 23 districts in 03 major (07 sub) clusters. These SOM clusters were projected in the geographical space and based on the disease/cases intensity the districts were characterized into low, medium and high endemic areas. Conclusion This visualization approach, SOM-GIS helps the public health officials to identify the disease endemic zones and take real time decisions for disease management