Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria

Malaria Journal

Research

Geoffrey L. Johnston¹  John H. Huber²  T. Alex Perkins³  Bryan Greenhouse⁴  David L. Smith⁵ 

[1] Apple Inc., Cupertino, CA, USA;Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA;Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA;Department of Medicine, University of California, San Francisco, CA, USA;Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA;

关键词: Epidemiology;    Malaria elimination;    Mathematical model;    Statistical inference;   

DOI  :  10.1186/s12936-016-1537-6

 received in 2016-06-15, accepted in 2016-09-14,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundThe serial interval is a fundamentally important quantity in infectious disease epidemiology that has numerous applications to inferring patterns of transmission from case data. Many of these applications are apropos of efforts to eliminate falciparum malaria from locations throughout the world, yet the serial interval for this disease is poorly understood quantitatively.MethodsTo obtain a quantitative estimate of the serial interval for falciparum malaria, the sum of the components of the falciparum malaria transmission cycle was taken based on a combination of mathematical models and empirical data. During this process, a number of factors were identified that account for substantial variability in the serial interval across different contexts.ResultsTreatment with anti-malarial drugs roughly halves the serial interval due to an abbreviated period of human infectiousness, seasonality results in different serial intervals at different points in the transmission season, and variability in within-host dynamics results in many individuals whose serial intervals do not follow average behaviour. Furthermore, 24.5 % of secondary cases presenting clinically did so prior to the primary cases being identified through active detection of infection.ConclusionsThese results have important implications for epidemiological applications that rely on quantitative estimates of the serial interval of falciparum malaria and other diseases characterized by prolonged infections and complex ecological drivers.

【 授权许可】

CC BY   
© The Author(s) 2016