Search

Background: The COVID-19 pandemic has global impacts but is relatively understudied in developing countries. Mongolia, a lower-middle-income country, instituted strict control measures in early 2020 and avoided widespread transmission until vaccines became available in February, 2021. Mongolia achieved its 60% vaccination coverage goal by July 2021. We investigated the distribution and determinants of SARS-CoV-2 seroprevalence in Mongolia over 2020 and 2021., Methods: We performed a longitudinal seroepidemiologic study aligned with WHO's Unity Studies protocols. We collected data from a panel of 5000 individuals in four rounds between October 2020 and December 2021. We selected participants through local health centres across Mongolia by age-stratified multi-stage cluster sampling. We tested serum for the presence of total antibodies against SARS-CoV-2 receptor-binding domain, and levels of anti-SARS-CoV-2 spike IgG and neutralising antibodies. We linked participant data with national mortality, COVID-19 case, and vaccination registries. We estimated population seroprevalence and vaccine uptake, as well as unvaccinated population prior-infection prevalence., Findings: At the final round in late 2021, 82% (n = 4088) of participants completed follow-up. Estimated seroprevalence increased from 1.5% (95% CI: 1.2-2.0), to 82.3% (95% CI: 79.5-84.8) between late-2020 and late-2021. At the final round an estimated 62.4% (95% CI: 60.2-64.5) of the population were vaccinated, and of the unvaccinated population 64.5% (95% CI: 59.7-69.0) had been infected. Cumulative case ascertainment in the unvaccinated was 22.8% (95% CI: 19.1%-26.9%) and the overall infection-fatality ratio was 0.100% (95% CI: 0.088-0.124). Health workers had higher odds for being COVID-19 confirmed cases at all rounds. Males (1.72 (95% CI: 1.33-2.22)) and adults aged 20 and above (12.70 (95% CI: 8.14-20.26)) had higher odds for seroconverting by mid-2021. Among the seropositive, 87.1% (95% CI: 82.3%-90.8%) had SARS-CoV-2 neutralising antibodies by late 2021., Interpretation: Our study enabled tracking of SARS-CoV-2 serological markers in the Mongolian population over one year. We found low SARS-CoV-2 seroprevalence in 2020 and early 2021, with seropositivity increasing over a 3-month interval in 2021 due to vaccine roll out and rapid infection of most of the unvaccinated population. Despite high seroprevalence in Mongolia amongst both vaccinated and unvaccinated individuals by end-2021, the SARS-CoV-2 Omicron immune escape variant caused a substantial epidemic., Funding: World Health Organization, WHO UNITY Studies initiative, with funding by the COVID-19 Solidarity Response Fund and the German Federal Ministry of Health (BMG) COVID-19 Research and development. The Ministry of Health, Mongolia partially funded this study., Competing Interests: We declare no competing interests., (© 2023 World Health Organization.)

Competing Interests: The authors declare no conflicts of interest. The modelling work was supported by the World Health Organization Regional Office for the Western Pacific to provide modelling advice to Member States. Authors HAN and TAN were supported by funding from the Department of Foreign Affairs and Trade (DFAT), Australia.

Background: With the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in early 2020, Mongolia implemented rapid emergency measures and did not report local transmission until November 2020. We conducted a national seroprevalence survey to monitor the burden of SARS-CoV-2 in Mongolia in the months surrounding the first local transmission., Methods: During October-December 2020, participants were randomly selected using age stratification and invited for interviews and blood samples at local primary health centres. We screened for total SARS-CoV-2 antibodies, followed by two-step quantitative SARS-CoV-2 IgG serology tests for positive samples. Weighted and test-adjusted seroprevalences were estimated. We used chi-square, Fisher's exact and other tests to identify variables associated with seropositivity., Findings: A total of 5000 subjects were enrolled. We detected SARS-CoV-2 IgG antibodies in 72 samples. Crude seroprevalence of SARS-CoV-2 antibodies was 1·44% (95%CI,1·21-1·67). Population weighted and test-adjusted seroprevalences were 1·36% (95%CI,1·11-1·63) and 1·45% (95%CI,1·11-1·63), respectively. Age, sex, geographical, and occupational factors were not associated with seropositivity (p>0·05). Symptoms and signs within past 3 months and seropositivity were not associated at the time of the survey (p>0·05)., Interpretation: SARS-CoV-2 seroprevalence in Mongolia was low in the first year of the pandemic potentially due to strong public health measures, including border restrictions, educational facilities closure, earlier adoption of mask-wearing and others. Our findings suggest large-scale community transmission could not have occurred up to November 2020 in Mongolia. Additional serosurveys are needed to monitor the local pandemic dynamic and estimate how far from herd immunity Mongolia will be following-up with vaccination programme in 2021 and 2022., Funding: World Health Organisation, WHO UNITY Studies initiative, with funding by the COVID-19 Solidarity Response Fund and the German Federal Ministry of Health (BMG) COVID-19 Research and development., Translation: Cyrillic and Traditional Mongolian translation of abstract is available on appendix section., Competing Interests: None., (© 2021 The Authors.)

Background: COVID-19 initially caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with many high-income countries, possibly because of differing demographics, socioeconomics, surveillance, and policy responses. Here, we investigate the role of multiple factors on COVID-19 dynamics in the Philippines, a LMIC that has had a relatively severe COVID-19 outbreak., Methods: We applied an age-structured compartmental model that incorporated time-varying mobility, testing, and personal protective behaviors (through a "Minimum Health Standards" policy, MHS) to represent the first wave of the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon, Central Visayas, and the National Capital Region). We estimated effects of control measures, key epidemiological parameters, and interventions., Findings: Population age structure, contact rates, mobility, testing, and MHS were sufficient to explain the Philippines epidemic based on the good fit between modelled and reported cases, hospitalisations, and deaths. The model indicated that MHS reduced the probability of transmission per contact by 13-27%. The February 2021 case detection rate was estimated at ~8%, population recovered at ~9%, and scenario projections indicated high sensitivity to MHS adherence., Interpretation: COVID-19 dynamics in the Philippines are driven by age, contact structure, mobility, and MHS adherence. Continued compliance with low-cost MHS should help the Philippines control the epidemic until vaccines are widely distributed, but disease resurgence may be occurring due to a combination of low population immunity and detection rates and new variants of concern., Competing Interests: Robert Neil F. Leong has received funding from the World Health Organization (WHO) Western Pacific Regional Office (WPRO) to conduct COVID-19 modelling work for select South-East Asian countries. He has served as a co-Investigator of the Foundation for Innovative New Diagnostics where he conducted a market landscaping study for point-of-care GeneXpert machines for gonorrhea and chlamydia and these machines are currently considered for COVID-19 use. He has been contracted, but services has not yet commenced, for technical secretariat services solely for the DSMB as part of the Phase IV clinical trial of Sinovac in the Philippine-leg (Sinovac by Biotech Ltd. through PiVOT Philippines). Richard Gray received funding from the WHO WPRO to conduct COVID-19 modelling work and provide support to countries in the region during 2020 and received additional funding from WHO for research outside the scope of this work. He received funding from the Australian Government Department of Health and the New South Wales (NSW) Department of Health, Corrective Services NSW, and Justice and Mental Health Network NSW for research outside of this work. He is a participant in the UNAIDS HIV Estimates and Projections Reference Group and he provided non-funded project advice for Gilead and ViiV. James Wood received funding from WHO WPRO for COVID-19 research, of which this project was one aspect. He also received funding from the Australian Government Department of Health to support modelling contributions to Australian COVID-19 responses in 2020. James Trauer received funding from the WHO related to this work and various other COVID-19 modelling projects., (© 2021 Published by Elsevier Ltd.)