A demographic model of measles epidemics

Analysis of the yearly transition function in measles disease modeling

Globally, there were an estimated 9.8 million measles cases and 207 500 measles deaths in 2019. As the effort to eliminate measles around the world continues, modeling remains a valuable tool for public health decision-makers and program implementers. This study presents a novel approach to the use of a yearly transition function that formulates mathematically the vaccine schedules for different age groups while accounting for the effects of the age of vaccination, the timing of vaccination, and disease seasonality on the yearly number of measles cases in a country. The methodology presented adds to an existing modeling framework and expands its analysis, making its utilization more adjustable for the user and contributing to its conceptual clarity. This article also adjusts for the temporal interaction between vaccination and exposure to disease, applying adjustments to estimated yearly counts of cases and the number of vaccines administered that increase population immunity. These new model features provide the ability to forecast and compare the effects of different vaccination timing scenarios and seasonality of transmission on the expected disease incidence. Although the work presented is applied to the example of measles, it has potential relevance to modeling other vaccine-preventable diseases.

Evolution and Use of Dynamic Transmission Models for Measles and Rubella Risk and Policy Analysis

The devastation caused by periodic measles outbreaks motivated efforts over more than a century to mathematically model measles disease and transmission. Following the identification of rubella, which similarly presents with fever and rash and causes congenital rubella syndrome (CRS) in infants born to women first infected with rubella early in pregnancy, modelers also began to characterize rubella disease and transmission. Despite the relatively large literature, no comprehensive review to date provides an overview of dynamic transmission models for measles and rubella developed to support risk and policy analysis. This systematic review of the literature identifies quantitative measles and/or rubella dynamic transmission models and characterizes key insights relevant for prospective modeling efforts. Overall, measles and rubella represent some of the relatively simplest viruses to model due to their ability to impact only humans and the apparent life-long immunity that follows survival of infection and/or protection by vaccination, although complexities arise due to maternal antibodies and heterogeneity in mixing and some models considered potential waning immunity and reinfection. This review finds significant underreporting of measles and rubella infections and widespread recognition of the importance of achieving and maintaining high population immunity to stop and prevent measles and rubella transmission. The significantly lower transmissibility of rubella compared to measles implies that all countries could eliminate rubella and CRS by using combination of measles- and rubella-containing vaccines (MRCVs) as they strive to meet regional measles elimination goals, which leads to the recommendation of changing the formulation of national measles-containing vaccines from measles only to MRCV as the standard of care.

Effect of thermal environment on the temporal, spatial and seasonal occurrence of measles in Ondo state, Nigeria

We investigated the temporal and spatial dynamics, as well as the seasonal occurrence of measles in Ondo state, Nigeria, to better understand the role of the thermal environment in the occurrence of the childhood killer disease measles, which ranks among the top ten leading causes of child deaths worldwide. The linkages between measles and atmospheric environmental factors were examined by correlating human-biometeorological parameters in the study area with reported clinical cases of measles for the period 1998-2008. We also applied stepwise regression analysis in order to determine the human-biometeorological parameters that lead to statistical changes in reported clinical cases of measles. We found that high reported cases of measles are associated with the least populated areas, where rearing and cohabitation of livestock/domestic animals within human communities are common. There was a significant correlation (P < 0.01) between monthly cases of measles and human-biometeorological parameters except wind speed and vapour pressure. High transmission of measles occurred in the months of January to May during the dry season when human thermal comfort indices are very high. This highlights the importance of the thermal environment in disease demographics since it accounted for more than 40% variation in measles transmission within the study period.