INTRODUCTION
Though much is known about SARS-CoV-2 since it was first described in Wuhan at the end of 2019, there is insufficient knowledge of the evolution of transmission trends, infectivity and the changing pathophysiology of the COVID-19 disease that it causes. Emergency Use Authorization of multiple vaccine candidates and their rapid deployment in many regions of the globe provide some insights into the possibilities of controlling the spread of the disease and reducing rates of severe manifestations of the disease, hospitalizations and death.
Any exercise to predict the future trends of the transmission of infection, the evolution of transmissibility (contagiousness) and the changing pathogenesis and presentation of COVID-19 in population subsets must be done with both caution and spades of humility.
Many factors influence the way in which we navigate our way through figuring out what we are likely to face over the coming period. Host, pathogen and environmental factors all contribute to the evolution of the pandemic in the local context.
Natural immunity and vaccination coverage are critical host factors. Whilst both these factors will contribute to the size and shape of future spread, they have not been sufficiently enlightening for our third wave experience. Natural immunity in Gauteng resulting from the second wave varies considerably from 5-43% (Mahdi) across the provincial locales and there is some evidence of sub-district variation (up to 71%) arising out of prior natural immunity from the first wave (Myers). The ability of variants of concern (VOC) to partially escape both natural and vaccine-induced immunity is difficult to estimate and weakens the predictive value of prior COVID-19 infection and vaccination status.
Age, co-morbidities and body mass index (BMI) are other important host factors to take into account in efforts to forecast disease severity. Unfortunately, outside of the Western Cape Province and the medical schemes members, almost no systematic data exists to fathom their effect. Social class is likely to feature as a factor in health status, agency to control exposure and health care options including access to home-based treatment alternatives such as oxygen concentrators, and even access to vaccination.
Population density, mobility and modes of transport are also important factors that fuel transmission. It is difficult to measure the impact of these factors on transmission dynamics though a common wisdom is emerging that indoor gatherings and nighttime movement are important factors in driving new infections. Hence, the focus on gatherings and the curfew in the recent Alert Lockdown Level 4 announcement.
What is more difficult to fathom are seeding events and wave triggers. Seeding events that lead to cluster outbreaks in the home, shopping centres or congregant settings are due both to chance and to human behavior. The sequence of events that lead clusters to coalesce to a critical tipping point that then sets of a wave is less well understood. What triggered the second wave in the Eastern Cape? And why did the Northern Cape come first in the third wave? Factors such as population density and the geographic spacing of small towns in rural provinces and regions are likely to affect the height of the peak, the rate of its rise and fall and the duration of the wave. It is likely that the Delta variant that is more transmissible than other variants shows a rapid rise to a high peak and a precipitous fall as seen in the India second wave or the second wave in Portugal (due to the Alpha variant which was similarly more transmissible than the ancestry virus). We have not yet seen the peak in Gauteng yet but the rise is clearly due to the Delta variant based on the latest genomic analysis reports.
Winter and summer were initially expected to play a role in the timing of waves in the way that seasonal changes drive the annual influenza epidemic; but this is no longer believed to have any influence on the timing of waves, which seem to be bi-annual every 6 months with low levels of NPIs or more protracted across many months of the year if strict NPIs are possible. All of this gives rise to serious unpredictability even though there might be some knowns which may be summed up as the pandemic continuing everywhere until substantive vaccine coverage is achieved.
Having stated the shortcomings of our knowledge and know-how in the introduction, we are able to turn our attention to what we have learned about this pandemic, in an attempt to figure out what is likely to unfold over the medium term. The analysis of available data and a discussion explaining how we may use this analysis is set out below.
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