Revealing Measles Outbreak Risk With a Nested Immunoglobulin G Serosurvey in Madagascar

Abstract

Madagascar reports few measles cases annually and high vaccination campaign coverage. However, the underlying age profile of immunity and risk of a measles outbreak is unknown. We conducted a nested serological survey, testing 1,005 serum samples (collected between November 2013 and December 2015 via Madagascar’s febrile rash surveillance system) for measles immunoglobulin G antibody titers. We directly estimated the age profile of immunity and compared these estimates with indirect estimates based on a birth cohort model of vaccination coverage and natural infection. Combining these estimates of the age profile of immunity in the population with an age-structured model of transmission, we further predicted the risk of a measles outbreak and the impact of mitigation strategies designed around supplementary immunization activities. The direct and indirect estimates of age-specific seroprevalence show that current measles susceptibility is over 10%, and modeling suggests that Madagascar may be at risk of a major measles epidemic.

Towards better targeting: lessons from a posthoneymoon measles outbreak in Madagascar, 2018–2019

“…In September 2018, a cluster of laboratory-confirmed measles cases was detected via Madagascar's national febrile/rash surveillance system for measles and rubella, whereby local health centres send samples taken from suspected cases in to the national reference lab in Antananarivo. [6][7][8] At that time, the positivity rate of measles suspected cases reached 2.12% every year compared with an average of 0.54% during the last previous 5 years (ranged from 0.22% to 0.95%). By October 2018, increasing numbers of measles cases were detected by the health system (figure 1B).…”

“…This could allow faster epidemic growth in these regions. Comparing the early growth of the epidemic estimated using R E (or the number of new infections per infectious individual 6 ) indicates that, indeed, the outbreak grew faster in some regions with historically high levels of vaccine coverage (figure 2B).…”

“…Second, existing convenience serological samples (eg, fever-rash surveillance for which samples are already available) could be leveraged to test for population immunity to measles. This approach had been applied to existing fever-rash surveillance in Madagascar, and did indeed suggest important outbreak risk in Madagascar prior to 2018 outbreak, 6 as a result of accumulation of susceptible individuals resulting from a combination of low circulation and incomplete vaccination coverage. However, convenience samples of this type are generally spatially variable, and thus may be non-representative.…”

Using Serology to Anticipate Measles Post-honeymoon Period Outbreaks

“…A crosssectional population serological survey was harnessed to launch a vaccination campaign and thus avert a post-honeymoon outbreak in England and Wales [11]. More recently, analysis of a serological convenience sample taken from fever/rash surveillance estimated a large susceptible population in Madagascar, suggesting the country had been experiencing a `honeymoon period' and was at considerable risk of a measles outbreak [12]. This subsequently occurred ( Figure 1A).…”

“…We can approach this problem via two immediately available sources of samples, allowing increasing granularity of prediction; there is also potential for a much more comprehensive approach. First, samples that could be leveraged for serological analysis are often available, collected as part of efforts for routine surveillance (such as fever and rash surveillance [12]), and stored at national reference laboratories in countries around the world. Second, large cross-sectional surveys [11] that include blood samples taken to test for other health outcomes (e.g., HIV prevalence studies) are widespread, often multi-national (e.g., the Demographic Health Surveys) and may be repeated across years, providing the important perspective of changes across time.…”