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

Abstract

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.

Chaotic dynamics in the seasonally forced SIR epidemic model

“…However, the transmission rate of many childhood infections and seasonal influenza abruptly changes by the host behaviour (cycles of human aggregation from school holidays, migrations, etc). Motivated by Diedrichs et al (2014), Olinky et al (2008), Uziel and Stone (2012), Keeling and Grenfell (1997), Thompson (2016), Earn et al (2000) we assume that φ can be expressed as…”

Delineating morbillivirus entry, dissemination and airborne transmission by studying in vivo competition of multicolor canine distemper viruses in ferrets

“…Studies in mice and NHPs have shown that MV initially infects alveolar macrophages and DCs in the lungs, instead of epithelial cells of the upper respiratory tract [22–24]. Even though this is a possible entry route, it seems unlikely that a highly contagious virus with an R 0 of 12–18 [25] and of which infection with one 50% tissue culture infectious dose (TCID 50 ) is sufficient to cause productive infection in macaques [26], exclusively depends on infection of target cells in the alveoli. Additional routes of entry into a susceptible host have been postulated, including infection of CD150 + immune cells within the epithelium of the respiratory tract [18, 27].…”

Modeling the Transmission of Measles and Rubella to Support Global Management Policy Analyses and Eradication Investment Cases

“…Recognizing the variability in current national measles and rubella immunization programs, experience with historical immunization, population structures, and viral transmission conditions, we model each area separately and then aggregate the results to regional and global levels. The model includes 180 WHO member states and three other areas (i.e., Puerto Rico, Hong Kong, and Macao) for which we found sufficient demographic and immunization data .…”

“…When outbreaks occur, some countries conduct outbreak response immunization (ORI) (i.e., outbreak SIAs [oSIAs]) and/or other public health interventions (e.g., contact tracing and isolation). Existing models for measles and rubella consider a wide range of different assumptions about the nature of immunity, transmission, population mixing, seasonality, heterogeneity, and other factors applied to real and hypothetical populations on different geographic scales . Within the last 15 years, analysts demonstrated the importance of using dynamic disease models to appropriately characterize the economic and policy impacts of interventions on population immunity for transmissible infectious diseases .…”

“…A 2016 study provided a best estimate of the global burden of congenital rubella syndrome (CRS) annual cases of approximately 105,000 (95% confidence interval of 54,000–158,000) . No existing models simultaneously track the dynamic transmission of measles and rubella to support analyses of regional or global control or elimination and prospective risk management options . To support efforts to prepare investment cases for measles and rubella to explore a range of future global management options, we developed a dynamic disease transmission model that tracks measles and rubella virus transmission within a modeled area, and we model WHO member states separately then aggregate the results to the global level.…”