BACKGROUND & OBJECTIVES: The present study aimed to systematically quantify the well known risk of severe dengue during secondary infection in literature and to understand how epidemiological mechanisms of enhancement during the secondary infection influence the empirically estimated risk of severe dengue by means of mathematical modeling. METHODS: Two conditional risks of severe dengue, i.e. symptomatic illness and dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), given secondary infection were explored based on systematically searched prospective studies. A two-strain epidemiological model was employed to simulate the transmission dynamics of dengue and to identify the relevant data gaps in empirical observations. RESULTS: Using the variance-based weighting, the pooled relative risk (RR) of symptomatic illness during secondary infection was estimated at 9.4 [95% confidence interval (CI): 6.1-14.4], and similarly, RR of DHF/DSS was estimated to be 23.7 (95% CI: 15.3-36.9). A variation in the RR of DHF/DSS was observed among prospective studies. Using the mathematical modeling technique, we identified the duration of cross-protective immunity as an important modulator of the time-dependent behaviour of the RR of severe dengue. Different epidemiological mechanisms of enhancement during secondary infection yielded different RR of severe dengue. INTERPRETATION & CONCLUSION: Optimal design of prospective cohort study for dengue should be considered, accounting for the time-dependence in the RR during the course of dengue epidemic. It is critical to statistically infer the duration of cross-protective immunity and clarify how the enhancement influences the epidemiological dynamics during secondary infection.
BACKGROUND & OBJECTIVES: The present study aimed to systematically quantify the well known risk of severe dengue during secondary infection in literature and to understand how epidemiological mechanisms of enhancement during the secondary infection influence the empirically estimated risk of severe dengue by means of mathematical modeling. METHODS: Two conditional risks of severe dengue, i.e. symptomatic illness and dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), given secondary infection were explored based on systematically searched prospective studies. A two-strain epidemiological model was employed to simulate the transmission dynamics of dengue and to identify the relevant data gaps in empirical observations. RESULTS: Using the variance-based weighting, the pooled relative risk (RR) of symptomatic illness during secondary infection was estimated at 9.4 [95% confidence interval (CI): 6.1-14.4], and similarly, RR of DHF/DSS was estimated to be 23.7 (95% CI: 15.3-36.9). A variation in the RR of DHF/DSS was observed among prospective studies. Using the mathematical modeling technique, we identified the duration of cross-protective immunity as an important modulator of the time-dependent behaviour of the RR of severe dengue. Different epidemiological mechanisms of enhancement during secondary infection yielded different RR of severe dengue. INTERPRETATION & CONCLUSION: Optimal design of prospective cohort study for dengue should be considered, accounting for the time-dependence in the RR during the course of dengue epidemic. It is critical to statistically infer the duration of cross-protective immunity and clarify how the enhancement influences the epidemiological dynamics during secondary infection.
Authors: Peter B Gilbert; Ying Huang; Michal Juraska; Zoe Moodie; Youyi Fong; Alexander Luedtke; Yingying Zhuang; Jason Shao; Lindsay N Carpp; Nicholas Jackson; Laurent Chambonneau; Alain Bouckenooghe; Betzana Zambrano; Carina Frago; Sophie Pallardy; Fernando Noriega Journal: Am J Trop Med Hyg Date: 2019-07 Impact factor: 2.345
Authors: Alastair I Matheson; Ondari D Mogeni; Joshua R Lacsina; Melvin Ochieng; Allan Audi; Godfrey Bigogo; John Neatherlin; Harold S Margolis; Barry Fields; Petronella Ahenda; Judd L Walson; Joel M Montgomery Journal: Am J Trop Med Hyg Date: 2020-11 Impact factor: 2.345