Access to healthcare as an important moderating variable for understanding the geography of COVID-19 outcomes – preliminary insights from Poland

Introduction: Biases in the measurement of COVID-19 burden and the uncertainty in estimation of the corresponding epidemiologic indexes are known and common phenomena in infectious diseases. We investigated to what extent healthcare access (HCA)-related supply/demand interfered with the registered data on COVID-19 in Poland. Material and Methods: We ran a multiple linear regression model with interactions to explain the geographic variation in seroprevalence, hospitalizations (on the voivodeship – NUTS-2 level) and current (beginning of the 4th wave of COVID cases – 15.09-21.11.2021) case notifications/crude mortality (on poviat – old NUTS-4 level). We took vaccination coverage and cumulative case notifications up to the so called 3rd wave as predictor variables and supply/demand (HCA) as moderating variables. Results: HCA with interacting terms (mainly demand) explained to the great extent the variance of current incidence and most of the variance in the current mortality rates. HCA (mainly supply) was significantly moderating cumulative case notifications until the 3rd wave of cases, thus explaining the variance in seroprevalence and hospitalization. Conclusion: Seeking causal relations between the vaccinationor infection-gained immunity level and the current infection dynamics could be misleading without understanding the socio-epidemiologic context such as the moderating role of HCA (sensu lato). After quantification, HCA could be incorporated into epidemiologic models for improved prediction of the actual disease burden.