Adult learning and education as a tool to contain pandemics: The COVID-19 experience

Abstract

In combating pandemics, more can be gained by changing citizens' behaviours than by relying solely on the medical route. In the current COVID-19 pandemic, the struggle to contain the outbreak and push back new infection figures will ultimately be won by training citizens how to avoid creating secondary transmission chains. The COVID-19 pandemic highlights the relationship between individual behaviour and group risk. Mass training of all social strata of a country's entire population is therefore critical in mitigating the pandemic. The authors of this article argue that adult learning and education (ALE) can play a pivotal role particularly in countries where average literacy levels are low, as these are usually the same countries in which healthcare systems are more fragile. This article explains why ALE, especially the promotion of health literacy as part of ALE (which is itself part of lifelong learning), is necessary to enable individuals to make informed health-related decisions. Research has shown that low-or non-literate individuals are less responsive to health education, less likely to use disease prevention services, and less likely to successfully manage chronic disease than literate citizens. The authors refer to the evaluation of the health literacy aspect of a large-scale adult literacy campaign launched in South Africa in 2008 which has yielded measurable outcomes and proved that the intervention had enabled adults to better understand health messages. They stress the importance of populations having at least a basic level of literacy and numeracy skills to enable them to receive and act on vital information during a pandemic or disaster. They argue that ALE should in fact be understood as an inherent element of every national emergency strategy, both in terms of prior preparation for possible future emergencies (such as pandemics, earthquakes, tornados, flooding, bushfires etc.), and in terms of reaction to a given emergency such as the current COVID-19 pandemic.

Sars-Cov-2 Three Forcing Seasonalities: Policies, Environment and Urban Spaces

“…April, followed by other countries patterns. This was proved to be true [2][3][4][5][6][7][8] over time of pandemic outbreak regarding policies and SARS-COV-2 spreading patterns data. But it does not mean that environmental variables such as atmosphere properties or Earth seasonality present no causation on the event (this will not be demonstrated and it is only theoretically assumed for the long-term expression of the pandemics, of which we don't have still a visible glance of it).…”

“…Following this path, no periodic criterion was met for basic reproductive number stability for an endemic equilibrium. We are facing daily new cases worldwide (figure 4) and the reason for the north hemisphere for European and Asian countries reduces its spreading patterns in the end of winter season is rather a coincidence over time that was caused mainly due to policies and ALE over population and individual behavior [3][4][5][6][7][8]. If no seasonality of atmospheric conditions was found, we can observe still a seasonality forcing behavior, which was very well shaped by contact rates frameworks [4] based on policies and ALE actions [6] as represented in Figure 5.…”

“…Bell shaped curve scheme. This overall scenario of pandemics could be very well observed in late March and starting April when at that time China and South Korea were the countries with the most lower rates of exponential growth of infection while Europe was in its growing pattern fully active and also in later June, many other researches pointed to the importance and role of policies and ALE towards pandemic control rather than atmospheric patterns of infection spreading worldwide [2][3][4][5][6][7][8][9]. April, followed by other countries patterns.…”

“…This point can be addressed to the pattern formation of confounding forced seasonality for S and R compartments over time [1,[23][24][25][26][27][28][29], environmental driven factors [30][31][32] and policies/ALE intervention [3][4][5][6][7][8]. It is possible to observe (figure 1, 3 and 7) that each country dimension might respond differently to the same initial conditions, influenced by these three components, thus generating multiple patterns formation over time for SARS-COV-2 transmission and periodicity.…”

“…This new pattern formation of the epidemic behavior was well pointed by Duarte et al [34] when contact rate do not take in account weather conditions and time-varying aspects of epidemics. Therefore it was used an unpredictable shape (close to reality shapes), mainly defining this shape caused and asymptotic instabilities generated by S and R compartments over time [1,[23][24][25][26][27][28][29], environmental driven factors [30][31][32] and policies/ALE intervention [3][4][5][6][7][8]. This equation represents the presence of confounding and heterogeneous environmental variables with unknown predictive scale of or maximum likelihood estimator for due to nonlinear inputs for S and R (urban spaces), policies and environmental conditions influence, and therefore generating nonlinear outputs (asymptotic instability) [35,36].…”