OBJECTIVE: To evaluate the results obtained though intersectoral coordination and community empowerment in one study carried out during 6 years in Playa Municipality, Cuba. METHODS: A longitudinal assessment comparing one intervention and one control area was conducted. The intervention encompasses two main stages separated by two dengue outbreaks. The first stage, focused on strengthening intersectoral coordination, was initiated in January 2000. In August 2003, a complementary strategy, focused on community empowerment and was initiated in half of the intervention area. In the control area, routine dengue control activities continued without additional input. We used entomologic surveillance data from January 1999 to December 2005 to assess the effectiveness. We computed the Breteau index (BI) per health area and the 95% confidence interval for the difference between the BIs at each time point. A semiparametric mixed model to capture the evolution in time of Aedes aegypti larval densities was fitted. RESULTS: The BI in the control area showed the lowest value before starting the intervention. This was reversed 1 year after launching intersectoral activities for dengue control in the intervention area. In spite of spraying actions in all areas, the differences in BI between intervention and control areas remain significant until December 2002. Although for the next 2 years no differences were observed, they become significant again in December 2004, which corresponds with the implementation of the complementary community-based vector control strategy in the intervention area. CONCLUSIONS: The model fitted identified monotonous trends over time and reversal trends at particular moments. The confidence bands indicate sections with significant differences between areas. Our data increase the evidence that the intersectoral coordination and community empowerment strategy for A. aegypti control is effective.
OBJECTIVE: To evaluate the results obtained though intersectoral coordination and community empowerment in one study carried out during 6 years in Playa Municipality, Cuba. METHODS: A longitudinal assessment comparing one intervention and one control area was conducted. The intervention encompasses two main stages separated by two dengue outbreaks. The first stage, focused on strengthening intersectoral coordination, was initiated in January 2000. In August 2003, a complementary strategy, focused on community empowerment and was initiated in half of the intervention area. In the control area, routine dengue control activities continued without additional input. We used entomologic surveillance data from January 1999 to December 2005 to assess the effectiveness. We computed the Breteau index (BI) per health area and the 95% confidence interval for the difference between the BIs at each time point. A semiparametric mixed model to capture the evolution in time of Aedes aegypti larval densities was fitted. RESULTS: The BI in the control area showed the lowest value before starting the intervention. This was reversed 1 year after launching intersectoral activities for dengue control in the intervention area. In spite of spraying actions in all areas, the differences in BI between intervention and control areas remain significant until December 2002. Although for the next 2 years no differences were observed, they become significant again in December 2004, which corresponds with the implementation of the complementary community-based vector control strategy in the intervention area. CONCLUSIONS: The model fitted identified monotonous trends over time and reversal trends at particular moments. The confidence bands indicate sections with significant differences between areas. Our data increase the evidence that the intersectoral coordination and community empowerment strategy for A. aegypti control is effective.
Authors: Natarajan Arunachalam; Brij Kishore Tyagi; Miriam Samuel; R Krishnamoorthi; R Manavalan; Satish Chandra Tewari; V Ashokkumar; Axel Kroeger; Johannes Sommerfeld; Max Petzold Journal: Pathog Glob Health Date: 2012-12 Impact factor: 2.894