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Background and objective: The study is based on hypothesis that whether continuous entomological surveillance of Ae. aegypti and simultaneous appropriate interventions in key containers during non-transmission (December–May) months would have any impact on breeding of Aedes and dengue cases during the following transmission months (June–November). The impact of the surveillance and intervention measures undertaken during non-transmission months were assessed by entomological indicators namely container index (CI), house index (HI), pupal index (PI) and breteau index (BI). Methods: A total of 28 localities of West Zone of Delhi with persistent dengue endemicity were selected for the study. Out of these localities, 20 were included in study group while other 8 localities were in control group. IEC and various Aedes breeding control activities were carried out in study group in both non-transmission and transmission season whereas control group did not have any such interventions during non-transmission months as per guidelines of MCD. These activities were undertaken by a team of investigators from NIMR and SDMC, Delhi. In control group, investigators from NIMR carried out surveillance activity to monitor the breeding of Aedes mosquito in localities. Results: Comparison of baseline data revealed that all indices in control and study group of localities were comparable and statistically non-significant (p>0.05). In both study and control groups, indices were calculated after pooling data on seasonal basis, i.e., transmission and non-transmission months for both years. The test of significance conducted on all the four indices, i.e., HI, PI, CI, and BI, revealed a significant difference (p<0.05) between the study group and control group during transmission and non-transmission months except in HI. Due to consistent intervention measures undertaken in non-transmission months in study group, reduction in CI, HI, BI and PI was observed 63%, 62%, 64% and 99% respectively during transmission months as compared to control group where increase of 59%, 102%, 73% and 71% respectively. As a result of reduction in larval indices, no dengue case (except one NS1) was observed in study group, whereas 38 dengue cases were observed in control group. Conclusion: Through this pilot study, it is concluded that proper intervention in non-transmission season reduces vector density and subsequently dengue cases in transmission season. [ABSTRACT FROM AUTHOR]

Background: Dengue is a major international public health concern, one of the most important arthropod-borne diseases. More than 3.5 billion people are at risk of dengue infection and there are an estimated 390 million dengue infections annually. This prolific increase has been connected to societal changes such as population growth and increasing urbanization generating intense agglomeration leading to proliferation of synanthropic mosquito species. Quantifying the spatio-temporal epidemiology of dengue in large cities within the context of a Geographic Information System is a first step in the identification of socio-economic risk factors. Methodology/Principal Findings: This Project has been approved by the ethical committee of Institut Pasteur. Data has been anonymized and de-identified prior to geolocalisation and analysis. A GIS was developed for Delhi, enabling typological characterization of the urban environment. Dengue cases identified in the Delhi surveillance system from 2008 to 2010 were collated, localised and embedded within this GIS. The spatio-temporal distribution of dengue cases and extent of clustering were analyzed. Increasing distance from the forest in Delhi reduced the risk of occurrence of a dengue case. Proximity to a hospital did not increase risk of a notified dengue case. Overall, there was high heterogeneity in incidence rate within areas with the same socio-economical profiles and substantial inter-annual variability. Dengue affected the poorest areas with high density of humans, but rich areas were also found to be infected, potentially because of their central location with respect to the daily mobility network of Delhi. Dengue cases were highly clustered in space and there was a strong relationship between the time of introduction of the virus and subsequent cluster size. At a larger scale, earlier introduction predicted the total number of cases. Conclusions/Significance: DENV epidemiology within Delhi has a forest fire signature. The stochastic nature of this invasion process likely smothers any detectable socio-economic risk factors. However, the significant finding that the size of the dengue case cluster depends on the timing of its emergence emphasizes the need for early case detection and implementation of effective mosquito control. A better understanding of the role of population mobility in contributing to dengue risk could also help focus control on areas at particular risk of dengue virus importation. [ABSTRACT FROM AUTHOR]