OBJECTIVES: A Centers for Disease Control and Prevention deviation bar chart (Statistical Software for Public Health Surveillance) and laboratory-based surveillance data were evaluated for their utility in detecting dengue outbreaks in Puerto Rico. METHODS: A significant increase in dengue incidence was defined as an excess of suspected cases of more than 2 SDs beyond the mean for all 4-week periods from April through June (the period of lowest seasonal incidence), 1989 through 1993. An outbreak was defined as a cumulative annual rate of reported dengue greater than 3 per 1000 population. RESULTS: Retrospective application of the system to 1994 data showed agreement with previous analyses. In 1995 and 1996, 36.4% and 27.3%, respectively, of municipalities with a significant increase in reports for 2 or more consecutive weeks before the first week of September had an outbreak, compared with 9.0% (in 1995, P = .042) and 6.0% (in 1996, P = .054) of towns without a significant increase. The system showed sensitivity near 40%, specificity near 89%, and accuracy in classifying municipalities near 84%. CONCLUSIONS: This method provides a statistically based, visually striking, specific, and timely signal for dengue control efforts.
OBJECTIVES: A Centers for Disease Control and Prevention deviation bar chart (Statistical Software for Public Health Surveillance) and laboratory-based surveillance data were evaluated for their utility in detecting dengue outbreaks in Puerto Rico. METHODS: A significant increase in dengue incidence was defined as an excess of suspected cases of more than 2 SDs beyond the mean for all 4-week periods from April through June (the period of lowest seasonal incidence), 1989 through 1993. An outbreak was defined as a cumulative annual rate of reported dengue greater than 3 per 1000 population. RESULTS: Retrospective application of the system to 1994 data showed agreement with previous analyses. In 1995 and 1996, 36.4% and 27.3%, respectively, of municipalities with a significant increase in reports for 2 or more consecutive weeks before the first week of September had an outbreak, compared with 9.0% (in 1995, P = .042) and 6.0% (in 1996, P = .054) of towns without a significant increase. The system showed sensitivity near 40%, specificity near 89%, and accuracy in classifying municipalities near 84%. CONCLUSIONS: This method provides a statistically based, visually striking, specific, and timely signal for dengue control efforts.
Authors: D M Morens; J G Rigau-Pérez; R H López-Correa; C G Moore; E E Ruiz-Tibén; G E Sather; J Chiriboga; D A Eliason; A Casta-Velez; J P Woodall Journal: Am J Trop Med Hyg Date: 1986-01 Impact factor: 2.345
Authors: Mark E Beatty; Amy Stone; David W Fitzsimons; Jeffrey N Hanna; Sai Kit Lam; Sirenda Vong; Maria G Guzman; Jorge F Mendez-Galvan; Scott B Halstead; G William Letson; Joel Kuritsky; Richard Mahoney; Harold S Margolis Journal: PLoS Negl Trop Dis Date: 2010-11-16
Authors: Jean-Paul Chretien; Howard S Burkom; Endang R Sedyaningsih; Ria P Larasati; Andres G Lescano; Carmen C Mundaca; David L Blazes; Cesar V Munayco; Jacqueline S Coberly; Raj J Ashar; Sheri H Lewis Journal: PLoS Med Date: 2008-03-25 Impact factor: 11.069
Authors: Tyler M Sharp; Kyle R Ryff; Gilberto A Santiago; Harold S Margolis; Stephen H Waterman Journal: Emerg Infect Dis Date: 2019-08 Impact factor: 6.883
Authors: Leigh R Bowman; Gustavo S Tejeda; Giovanini E Coelho; Lokman H Sulaiman; Balvinder S Gill; Philip J McCall; Piero L Olliaro; Silvia R Ranzinger; Luong C Quang; Ronald S Ramm; Axel Kroeger; Max G Petzold Journal: PLoS One Date: 2016-06-27 Impact factor: 3.240