Showing papers by "Anthony T. Newall published in 2018"

WHO guide on the economic evaluation of influenza vaccination.

Abstract: Influenza is responsible for substantial morbidity and mortality across the globe, with a large share of the total disease burden occurring in low- and middle-income countries (LMICs). There have been relatively few economic evaluations assessing the value of seasonal influenza vaccination in LMICs. The purpose of this guide is to outline the key theoretical concepts and best practice in methodologies and to provide guidance on the economic evaluation of influenza vaccination in LMICs. It outlines many of the influenza vaccine-specific challenges and should help to provide a framework for future evaluations in the area to build upon.

Rationale and opportunities in estimating the economic burden of seasonal influenza across countries using a standardized WHO tool and manual.

Abstract: Influenza disease burden is recognized as one of the major public health problems globally. Much less is known about the economic burden of influenza especially in low- and middle-income countries (LMICs). A recent systematic review on the economic burden of influenza in LMICs suggests that information is scarce and/or incomplete and that there is a lack of standardized approaches for cost evaluations in LMICs. WHO commissioned and publicized a Manual for estimating the economic burden of seasonal influenza to support the standardization of estimates of the economic burden of seasonal influenza across countries. This article aims to describe the rationale of this manual development and opportunities that lie in collecting data to help policymakers estimate the economic burden of seasonal influenza. It describes a manual developed by WHO to help such estimation and also links to relevant literature and tools to ensure robustness of applied methods to assess the economic burden associated with seasonal influenza, including direct medical costs, direct non-medical costs and indirect costs.

Influenza‐associated mortality in South Africa, 2009‐2013: The importance of choices related to influenza infection proxies

Abstract: Background Regression modeling methods are commonly used to estimate influenza-associated mortality using covariates such as laboratory-confirmed influenza activity in the population as a proxy of influenza incidence. Objective We examined the choices of influenza proxies that can be used from influenza laboratory surveillance data and their impact on influenza-associated mortality estimates. Method Semiparametric generalized additive models with a smoothing spline were applied on national mortality data from South Africa and influenza surveillance data as covariates to obtain influenza-associated mortality estimates from respiratory causes from 2009 to 2013. Proxies examined included alternative ways of expressing influenza laboratory surveillance data such as weekly or yearly proportion or rate of positive samples, using influenza subtypes, or total influenza data and expressing the data as influenza season-specific or across all seasons. Result Based on model fit, weekly proportion and influenza subtype-specific proxy formulation provided the best fit. The choice of proxies used gave large differences to mortality estimates, but the 95% confidence interval of these estimates overlaps. Conclusion Regardless of proxy chosen, mortality estimates produced may be broadly consistent and not statistically significant for public health practice.