Modelling the impact of population mobility, post-infection immunity and vaccination on SARS-CoV-2 transmission in the Dominican Republic

COVID-19 epidemic dynamics are driven by a complex interplay of factors including population behaviour, government interventions, new variants, vaccination campaigns and immunity from prior infections. We aimed to quantify the epidemic drivers of SARS-CoV-2 dynamics in the Dominican Republic, an upper-middle income country of 10.8 million people, and assess the impact of the vaccination campaign implemented in February 2021 in saving lives and averting hospitalisations. We used an age-structured, multi-variant transmission dynamic model to characterise epidemic drivers in the Dominican Republic and explore counterfactual scenarios around vaccination coverage and population mobility. We fit the model to reported deaths, hospital bed occupancy, ICU bed occupancy and seroprevalence data until December 2021 and simulated epidemic trajectories under different counterfactual vaccination scenarios. We estimate that vaccination averted 5040 hospital admissions (95% CrI: 4750 - 5350), 1500 ICU admissions (95% CrI: 1420 - 1590) and 544 deaths (95% CrI: 488 - 606) in the first 6 months of the campaign. We also found that early vaccination with Sinovac-CoronaVac was preferable to delayed vaccination using a product with higher efficacy. We investigated the trade-off between changes in vaccination coverage and population mobility to understand how much relaxation of social distancing measures vaccination was able to ‘buy’ in the later stages of a pandemic. We found that if no vaccination had occurred, an additional decrease of 10-20% in population mobility would have been required to maintain the same death and hospitalisation outcomes. We found SARS-CoV-2 transmission dynamics in the Dominican Republic were driven by substantial accumulation of immunity during the first two years of the pandemic but that, despite this, vaccination was essential in enabling a return to pre-pandemic mobility levels without incurring considerable additional morbidity and mortality. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement EF was supported by the Medical Research Council (MR/N013638/1); AJK was supported by Wellcome Trust (206250/Z/17/Z); RL was supported by a Royal Society Dorothy Hodgin Fellowship; EJK was supported by the US CDC (U01GH002238), CLL was supported by an Australian National Health and Medical Research Council Investigator Grant (APP1158469). CTP and RS-R are employees of the Ministry of Health and Social Assistance, Dominican Republic. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Secondary data analysis of COVID-19 data from the Dominican Republic was approved by the London School of Hygiene and Tropical Medicine Observational Research Ethics Committee (reference: 26214). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All code and data used for this analysis are available at: https://github.com/EmilieFinch/DR-covid19