Seasonal influence on respiratory tract infection severity including COVID‐19 quantified through Markov Chain modeling

Abstract

Respiratory tract infections (RTIs) are a burden to global health, but their characterization is complicated by the influence of seasonality on incidence and severity. The Re‐BCG‐CoV‐19 trial (NCT04379336) assessed BCG (re)vaccination for protection from coronavirus disease 2019 (COVID‐19) and recorded 958 RTIs in 574 individuals followed over 1 year. We characterized the probability of RTI occurrence and severity using a Markov model with health scores (HSs) for four states of symptom severity. Covariate analysis on the transition probability between HSs explored the influence of demographics, medical history, severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2), or influenza vaccinations, which became available during the trial, SARS‐CoV‐2 serology, and epidemiology‐informed seasonal influence of infection pressure represented as regional COVID‐19 pandemic waves, as well as BCG (re)vaccination. The infection pressure reflecting the pandemic waves increased the risk of RTI symptom development, whereas the presence of SARS‐CoV‐2 antibodies protected against RTI symptom development and increased the probability of symptom relief. Higher probability of symptom relief was also found in participants with African ethnicity and with male biological gender. SARS‐CoV‐2 or influenza vaccination reduced the probability of transitioning from mild to healthy symptoms. Model diagnostics over calendar‐time indicated that COVID‐19 cases were under‐reported during the first wave by an estimated 2.76‐fold. This trial was performed during the initial phase of the COVID‐19 pandemic in South Africa and the results reflect that situation. Using this unique clinical dataset of prospectively studied RTIs over the course of 1 year, our Markov Chain model was able to capture risk factors for RTI development and severity, including epidemiology‐informed infection pressure.

Risk Factors for COVID-19 and Respiratory Tract Infections during the Coronavirus Pandemic

“…This allowed us to better characterize the relationship between the reported COVID-19 burden and the occurrence of events. As expected, with a higher pandemic burden, the probability of having an event increased, which is consistent with our separate analysis describing the severity of RTIs+COVID-19 over time [29].…”

“…Firstly, only symptomatic events of COVID-19 cases diagnosed with a positive PCR or antigen test were used in the modeling, which potentially resulted in underreporting, because it was left to the participants to be tested or not. Additionally, while the model incorporated the reported COVID-19 burden, the hazard was not allowed to collapse to zero when the reported burden was approaching zero due to underreporting, especially at the beginning of the pandemic for which we have previously estimated the COVID-19 burden to be 2.76-fold higher than reported [ 29 ], likely because of the least amount of resources and diagnostics being available [ 47 ]. The extrapolation of the results in the future, outside of the context of the COVID-19 pandemic, must be done with care, as 25.7% of RTIs+COVID-19 events were confirmed as COVID-19, and this is likely a significant underestimation, as previously explored [ 27 ].…”

“…The reported COVID-19 burden for each district of interest, the City of Cape Town Metro and the Garden Route, corresponding to the Cape Town (TASK Central and University of Cape Town, South Africa) and TASK Eden sites, respectively, was extracted from the Western Cape Government COVID-19 dashboard [ 28 ]. Total cumulative COVID-19 cases (daily resolution) were transformed into new daily COVID-19 cases and rescaled per 10,000 capita for each respective district of interest, termed COVID-19 burden, and matched using the record date [ 29 ].…”

Reproducibility in pharmacometrics applied in a phase III trial of BCG-vaccination for COVID-19

“…A double-blind, randomized, placebo-controlled trial enrolled 1,000 health care workers to investigate this hypothesis (NCT04379336, Re-BCG-CoV-19 project 18 ). The primary endpoint of the trial was incidence of hospitalization due to COVID-19, with secondary endpoints including incidence of COVID-19, respiratory tract infection (RTI), and hospitalization due to all causes 19 . Participants were followed up for 52 weeks in the Western Cape, South Africa with the objective to assess in a timely manner if BCG (re)vaccination can reduce the COVID-19 burden on the health care system.…”