tetano
Editor, Senior Moderator
Am J Epidemiol. 2014 Sep 25. pii: kwu213. [Epub ahead of print]
Optimizing the Precision of Case Fatality Ratio Estimates Under the Surveillance Pyramid Approach.
Pelat C, Ferguson NM, White PJ, Reed C, Finelli L, Cauchemez S, Fraser C.
Abstract
In the management of emerging infectious disease epidemics, precise and accurate estimation of severity indices, such as the probability of death after developing symptoms-the symptomatic case fatality ratio (sCFR)-is essential. Estimation of the sCFR may require merging data gathered through different surveillance systems and surveys. Since different surveillance strategies provide different levels of precision and accuracy, there is need for a theory to help investigators select the strategy that maximizes these properties. Here, we study the precision of sCFR estimators that combine data from several levels of the severity pyramid. We derive a formula for the standard error, which helps us find the estimator with the best precision given fixed resources. We further propose rules of thumb for guiding the choice of strategy: For example, should surveillance of a particular severity level be started? Which level should be preferred? We derive a formula for the optimal allocation of resources between chosen surveillance levels and provide a simple approximation that can be used in thinking more heuristically about planning surveillance. We illustrate these concepts with numerical examples corresponding to 3 influenza pandemic scenarios. Finally, we review the equally important issue of accuracy.
? The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
KEYWORDS:
case fatality ratio; emerging infectious diseases; influenza; pandemics; statistical planning; surveillance protocol
PMID:
25255809
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/25255809
Optimizing the Precision of Case Fatality Ratio Estimates Under the Surveillance Pyramid Approach.
Pelat C, Ferguson NM, White PJ, Reed C, Finelli L, Cauchemez S, Fraser C.
Abstract
In the management of emerging infectious disease epidemics, precise and accurate estimation of severity indices, such as the probability of death after developing symptoms-the symptomatic case fatality ratio (sCFR)-is essential. Estimation of the sCFR may require merging data gathered through different surveillance systems and surveys. Since different surveillance strategies provide different levels of precision and accuracy, there is need for a theory to help investigators select the strategy that maximizes these properties. Here, we study the precision of sCFR estimators that combine data from several levels of the severity pyramid. We derive a formula for the standard error, which helps us find the estimator with the best precision given fixed resources. We further propose rules of thumb for guiding the choice of strategy: For example, should surveillance of a particular severity level be started? Which level should be preferred? We derive a formula for the optimal allocation of resources between chosen surveillance levels and provide a simple approximation that can be used in thinking more heuristically about planning surveillance. We illustrate these concepts with numerical examples corresponding to 3 influenza pandemic scenarios. Finally, we review the equally important issue of accuracy.
? The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
KEYWORDS:
case fatality ratio; emerging infectious diseases; influenza; pandemics; statistical planning; surveillance protocol
PMID:
25255809
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/25255809