A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2

Abstract

Despite various levels of preventive measures, in 2020, many countries have suffered severely from the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Using a model, we show that population heterogeneity can affect disease-induced immunity considerably because the proportion of infected individuals in groups with the highest contact rates is greater than that in groups with low contact rates. We estimate that if R0 = 2.5 in an age-structured community with mixing rates fitted to social activity, then the disease-induced herd immunity level can be ~43%, which is substantially less than the classical herd immunity level of 60% obtained through homogeneous immunization of the population. Our estimates should be interpreted as an illustration of how population heterogeneity affects herd immunity rather than as an exact value or even a best estimate.

Seroprevalence of Antibodies against SARS-CoV-2 among the Personnel and Students of the National and Kapodistrian University of Athens, Greece: A Preliminary Report

“…Nevertheless, the results presented herein in conjunction with available results from national or regional seroepidemiological studies in other countries, suggest that seroprevalence rates are far too low to reach protective (herd) immunity, which as estimated requires the presence of antibodies against SARS-CoV-2 in approximately 60% of the population [19,20].…”

IgG seroprevalence against SARS-CoV-2 in a cohort of 449 non-hospitalized, high-risk exposure individuals.

“…However, wide nationwide studies are reporting low seroprevalence rates 11,16,30 , which are promoting pessimistic perspectives between experts regarding the achievement of such herd immunity 31 . Noteworthy, the seroprevalence observed in our cohort indicates that the predominance of IgGs against SARS-CoV-2 may be quite heterogeneous between populations, and heterogeneity affects massively herd immunity, modulating the percentage of infected people required to reach it 10 . Therefore, seroprevalence studies in controlled settings as the one performed here could be really helpful to understand population heterogeneity related to herd immunity.…”

“…National governments are trying to screen their populations in an unbiased manner trying to identify and isolate infected people and to determine the actual rate of infection 9 . This information could be really informative as in an scenario of massive spreading of the virus, herd immunity could be achieved, that could help to control the community infection 10 . In this sense, the Spanish Ministry of Health has performed a massive seroprevalence study called ENE-COVID, analyzing the presence of anti-SARS-CoV-2 speci c IgG nationwide, including more than 60,000 people chosen randomly 11 .…”

COVID-19 Transmission Dynamics and Final Epidemic Size

“…Our model predictions are very consistent with ongoing disease data and the final epidemic size, implying that intervention strategies cannot be ignored. If control measures or population behaviors are relaxed, the second wave of infection may appear in the future [24].…”