Estimating efficacy of measles supplementary immunization activities via discrete-time modeling of disease incidence time series

10/17/2020
by   Tracy Qi Dong, et al.
0

Measles is a significant source of global disease burden and child mortality. Measles vaccination through routine immunization (RI) programs in high-burden settings remains a challenge due to poor health care infrastructure and access. Supplementary immunization activities (SIA) in the form of vaccination campaigns are therefore implemented to prevent measles outbreaks by reducing the size of the susceptible population. The SIA efficacy, defined as the fraction of susceptible population immunized by an SIA, is a critical metric for assessing campaign effectiveness. We propose a discrete-time hidden Markov model for estimating SIA efficacy and forecasting future incidence trends using reported measles incidence data. Our approach extends the time-series susceptible-infected-recovered (TSIR) framework by adding a model component to capture the impact of SIAs on the susceptible population. It also accounts for under-reporting and its associated uncertainty via a two-stage estimation procedure with uncertainty propagation. The proposed model can be used to estimate the underlying susceptible population dynamics, assess how many susceptible people were immunized by past SIAs, and forecast incidence trends in the future under various hypothetical SIA scenarios. We examine model performance via simulations under various levels of under-reporting, and apply the model to analyze monthly reported measles incidence in Benin from 2012 to 2018.

READ FULL TEXT

page 1

page 2

page 3

page 4

08/01/2020

Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case

The present paper introduces a new model used to study and analyse the s...
03/20/2020

Quantifying the under-reporting of genital warts cases

Genital warts are a common and highly contagious sexually transmitted di...
10/27/2021

Addressing delayed case reporting in infectious disease forecast modeling

Infectious disease forecasting is of great interest to the public health...
06/01/2016

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks

In retrospective assessments, internet news reports have been shown to c...
02/20/2019

Estimating and Forecasting the Smoking-Attributable Mortality Fraction for Both Sexes Jointly in 69 Countries

Smoking is one of the preventable threats to human health and is a major...
03/15/2018

Capturing Structure Implicitly from Time-Series having Limited Data

Scientific fields such as insider-threat detection and highway-safety pl...
01/21/2019

Forecasting mortality using Google trend

United State possesses the largest economy in the world, and thus serves...