Exploring affordable and effective pandemic containment measures in lower-income countries with a spatial SEIR model: a case study in South Africa

Abstract

Background: The COVID-19 pandemic has exposed the vulnerabilities of lower-income countries due to limited healthcare infrastructure and socioeconomic constraints, highlighting the need for effective containment measures that minimize socioeconomic costs and prepare for future pandemics alike, which are expected to become more frequent. Although prior studies have examined various strategies in these regions, a significant gap remains in quantitative research on affordable measures to combat the highly transmissible SARS-CoV-2 Omicron variant, which greatly challenges effective measures for previous strains. Studies on targeted containment measures for Omicron have dramatically declined even in higher-income regions, and their findings could be much less applicable in lower-income regions due to substantial socioeconomic disparities.

Methods: This study addresses this gap by focusing on South Africa. A spatial Susceptible-Exposed-Infected-Recovered (SEIR) model was developed to simulate the virus spread during the country's first Omicron wave from November 2021 to April 2022, integrating multisource statistics to overcome the typical scarcity of inter-city mobility data in lower-income countries. Three affordable containment measures were examined: (1) restricting inter-city mobility in epicenter provinces, while allowing nationwide intra-city movement for livelihood activities; (2) home isolation for positive cases, alongside quarantine for co-residents, accounting for high rates of asymptomatic cases, underreporting, and delays of self-isolation; and (3) prioritizing booster vaccinations for high-risk healthcare workers.

Results: The findings indicate that restricting inter-city mobility in the epicenter Gauteng, which only accounted for 3.6% of national mobility, could reduce national infections by 15.0%. Quarantining households with positive cases could reduce infections by 10.9%, despite the high rates of asymptomatic cases and presymptomatic transmission. Prioritizing booster vaccinations was also effective when healthcare workers had a much higher infection risk than others. Meanwhile, these measures incurred minimal socioeconomic costs compared to earlier pandemic strategies. Additionally, the spatial variation of containment measure effectiveness suggests that timely implementation of these measures before the infection rate escalates is critical for ensuring their effectiveness.

Conclusions: This research provides essential insights for lower-income countries to manage current and future pandemics within their economic and healthcare constraints, especially regarding targeted mobility restriction, quarantine, prioritized vaccination, and timing of containment measures.

Keywords: Affordable containment measures; Home quarantine; Lower-income countries; Mobility restriction; SARS-COV-2 Omicron variant.

Fig. 1

The cumulative number of COVID-19 infection cases in each municipality during the Omicron break from 25 November 2021 to 30 April 2022. The abbreviation of province names in this and subsequent figures: EC = Eastern Cape, FS = Free State, GT = Gauteng, KZN = KwaZulu-Natal, LIM = Limpopo, MP = Mpumalanga, NW = North West, NC = Northern Cape, WC = Western Cape

Fig. 2

a Origin–Destination matrix generated from South African inter-city travel flows, with scale bar indicating connection intensity. b Population flow data between provinces, regional flow data calculated from provincial travel data

Fig. 3

Structure of the spatial SEIR model used in this study. Deaths are not explicitly modeled, since the death rate of Omicron infections in South Africa was low (6.3‰ [38]) due to the relatively young demographic structure, which is common in lower-income countries. Also, the transfer from the Recovery group to the Susceptible group is not modeled, since the five-month simulation duration is shorter than the average immunity period after infection

Fig. 4

The observed and simulated population of the Infectious group (I_t) nationwide and in the municipality with the largest number of reported cases in each province. The effective reproduction number (R_e) values used in the simulations are based on provincial-level estimates reported by the National Institute for Communicable Diseases (NICD) of South Africa

Fig. 5

The simulated daily population of the Infectious group (I_t) in South Africa and the municipality with the most cases within Gauteng, KwaZulu-Natal, and the Western Cape provinces, under the basic scenario and four different inter-city travel restrictions

Fig. 6

Spatial distribution of simulated cumulative cases in the basic scenario and under different inter-city mobility restrictions

Fig. 7

The simulated daily population of the Infectious group (I_t) in South Africa, under the basic scenario (no isolation or quarantine), the scenario of only isolating reported cases, and the scenario of isolating reported cases as well as quarantining their households

Fig. 8

The simulated population of the Infectious group (I_t) with and without implementing prioritized vaccination for healthcare workers, when the infection and transmission risk of healthcare workers was set at (a) 3.4 times, and (b) 1.29 times that of the general population