Seroepidemiology and model-based prediction of SARS-CoV-2 in Ethiopia: longitudinal cohort study among front-line hospital workers and communities

Abstract

Background: Over 1 year since the first reported case, the true COVID-19 burden in Ethiopia remains unknown due to insufficient surveillance. We aimed to investigate the seroepidemiology of SARS-CoV-2 among front-line hospital workers and communities in Ethiopia.

Methods: We did a population-based, longitudinal cohort study at two tertiary teaching hospitals involving hospital workers, rural residents, and urban communities in Jimma and Addis Ababa. Hospital workers were recruited at both hospitals, and community participants were recruited by convenience sampling including urban metropolitan settings, urban and semi-urban settings, and rural communities. Participants were eligible if they were aged 18 years or older, had provided written informed consent, and were willing to provide blood samples by venepuncture. Only one participant per household was recruited. Serology was done with Elecsys anti-SARS-CoV-2 anti-nucleocapsid assay in three consecutive rounds, with a mean interval of 6 weeks between tests, to obtain seroprevalence and incidence estimates within the cohorts.

Findings: Between Aug 5, 2020, and April 10, 2021, we did three survey rounds with a total of 1104 hospital workers and 1229 community residents participating. SARS-CoV-2 seroprevalence among hospital workers increased strongly during the study period: in Addis Ababa, it increased from 10·9% (95% credible interval [CrI] 8·3-13·8) in August, 2020, to 53·7% (44·8-62·5) in February, 2021, with an incidence rate of 2223 per 100 000 person-weeks (95% CI 1785-2696); in Jimma Town, it increased from 30·8% (95% CrI 26·9-34·8) in November, 2020, to 56·1% (51·1-61·1) in February, 2021, with an incidence rate of 3810 per 100 000 person-weeks (95% CI 3149-4540). Among urban communities, an almost 40% increase in seroprevalence was observed in early 2021, with incidence rates of 1622 per 100 000 person-weeks (1004-2429) in Jimma Town and 4646 per 100 000 person-weeks (2797-7255) in Addis Ababa. Seroprevalence in rural communities increased from 18·0% (95% CrI 13·5-23·2) in November, 2020, to 31·0% (22·3-40·3) in March, 2021.

Interpretation: SARS-CoV-2 spread in Ethiopia has been highly dynamic among hospital worker and urban communities. We can speculate that the greatest wave of SARS-CoV-2 infections is currently evolving in rural Ethiopia, and thus requires focused attention regarding health-care burden and disease prevention.

Funding: Bavarian State Ministry of Sciences, Research, and the Arts; Germany Ministry of Education and Research; EU Horizon 2020 programme; Deutsche Forschungsgemeinschaft; and Volkswagenstiftung.

Figure 1

Map of Ethiopia showing the study sites Base map reproduced from OpenStreetMap and OpenStreetMap Foundation, under the Creative Commons Attribution-ShareAlike 4.0 International License. Blue represents urban areas; orange represents rural areas.

Figure 2

Study flow and point prevalence for SARS CoV-2 seropositivity in hospital workers recruited in Jimma and Addis Ababa (A) and in participants recruited from the general population in urban and rural Jimma and Addis Ababa (B) Data are n, n (%), seroprevalence (% and 95% credible interval), or mean (range). LTFU=lost to follow-up. *New seropositive incident refers to seropositive cases with previous negative serology result during round 1; new seropositive prevalent refers to seropositive cases that entered the study without a preceding diagnosis. † Additional 13 participants from Addis Ababa, nine of whom participated in two rounds and four of whom only participated in one round, were included but did not have data available for subcity. ‡New seropositive refers only to participants who were negative in one or more previous rounds, but became seropositive in the subsequent round, excluding new participants entering; therefore, the sum of new and previously seropositive participants does not always equal the total number of seropositive participants in that round.

Figure 2

Study flow and point prevalence for SARS CoV-2 seropositivity in hospital workers recruited in Jimma and Addis Ababa (A) and in participants recruited from the general population in urban and rural Jimma and Addis Ababa (B) Data are n, n (%), seroprevalence (% and 95% credible interval), or mean (range). LTFU=lost to follow-up. *New seropositive incident refers to seropositive cases with previous negative serology result during round 1; new seropositive prevalent refers to seropositive cases that entered the study without a preceding diagnosis. † Additional 13 participants from Addis Ababa, nine of whom participated in two rounds and four of whom only participated in one round, were included but did not have data available for subcity. ‡New seropositive refers only to participants who were negative in one or more previous rounds, but became seropositive in the subsequent round, excluding new participants entering; therefore, the sum of new and previously seropositive participants does not always equal the total number of seropositive participants in that round.

Figure 3

Seroprevalence over time for all six cohorts investigated in the study (A), and PCR test positivity rates and number of admissions to intensive care units due to COVID-19 in Ethiopia (B)

Figure 4

SEIR model of SARS-CoV-2 epidemic in Ethiopia (A) Compartments of the SEIR models and possible transition. (B) Model simulation of SEIR model for HW in Jimma Medical Center and St Paul's Hospital; data from round 1 and 2 were used for model training; later points, including round 3, were predictions. (C) Compartments of the extended SEIR models and possible transition; data from round 1 and 2 were used for model training; later points, including round 3, were predictions. (D) Model simulation of extended SEIR model for HW in Jimma Medical Center and St Paul's Hospital and community members in Jimma (combined) and Addis Ababa (combined); data from round 1 and 2 were used for model training; later points, including round 3, were predictions. HW=hospital workers. SEIR=susceptible, exposed, infectious, and recovered.

Figure 5

SEIR model of SARS CoV-2 epidemic in Ethiopia integrating the potential effect of exposure to a SARS-CoV-2 variant with immune escape potential (A) Topology of compartment model that allows for the infection with the variant of individuals who were exposed to the original virus. (B) Scaled test positivity rate (mapped from the complete country to the individual cities) and seroprevalence. The contribution of different variants is indicated, as well as the proportion of individuals exposed to both. SEIR=susceptible, exposed, infectious, and recovered.