The pandemic of COVID-19 continues to spread to new regions around the world, with over 9.17 million cases so far, and over 474,000 deaths. Scientists are trying to understand the factors that drive the risk of infection and poor outcomes. Now, a new study by researchers at the University of Louisville and Babson College and published on the preprint server medRxiv* in June 2020 describes the increased risk of COVID-19 deaths in spring, in the USA.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Weather and Disease Statistics
It is essential to understand how weather changes affect the incidence of COVID-19, the risk of hospitalization, and outcome. This could help predict increases in healthcare demand, so as to prepare at all levels for new waves of cases. It is also valuable to generate newer and better theories about the way the virus spreads and how to prevent transmission in relation to environmental factors.
Earlier studies on the influenza virus show that their spread is linked to temperature and humidity. Thus, in 2009 the H 1N1 virus spread was more significant in areas with low absolute humidity and open plan schools. On the other hand, the SARS-CoV was more likely to spread in colder areas, with more significant fluctuations in temperature, and greater wind speeds. The prevalence was highest at temperatures at about 62oF and relative humidity of 52%. With the MERS outbreak, the viral transmission was most significant with increased temperature and higher ultraviolet exposure.
Factors Affecting Viral Spread
For a virus to spread from one person to another, several conditions must be met. These include the right environmental conditions, close contact, and a vulnerable host, especially if the physical interactions and social behavior also encourage transmission. Due to these factors, the influenza virus spreads more on weekdays.
A similar trend was observed from the earliest studies in Wuhan, which showed that the spread was likely to be higher in thickly populated areas. Environmental factors are also important: for instance, air pollution can impair immunity and can increase the individual’s susceptibility to infection. When the particulate matter in the air is higher, the virus seems to stay airborne longer, and the increased duration of exposure could boost the death rates.
The period over which a virus survives also depends on the temperature, humidity, and virus concentration. The SARS-CoV-2 tends to die off faster at temperatures near 86ºF and low relative humidity. This applies to viral survival in the nasal secretions and mucous membranes as well.
In warm, humid conditions, the virus can live for seven days, and perhaps longer. The similarity between such conditions and the upper respiratory tract has led to the caution that in such circumstances, there could be an exponential rise in the viral spread.
Individual susceptibility depends on health, genetic constitution, dietary factors, and even residential location. The antigens to which a person is naturally exposed, as well as the level of sunlight, which boosts vitamin D levels, can also make a person more resistant to the virus.
The Study: COVID-19 Deaths and Weather In the US
With mixed results from various studies on the effects of weather on viral transmission, the current study focuses on using county-level COVID-19 mortality data from the whole of the country, as well as the recorded minimum-maximum temperatures around the time of exposure to the virus. Time-fixed effects are used as well as adjustment for serial correlations, the effect of social distancing, various air pollutant levels, and ultraviolet irradiation.
The researchers found about 87,770 deaths in the U.S. up to May 16, 2020, of which 60% were included in the current study. This comes to about 52,800 deaths. About 70% of the deaths in the study occurred in the northern region, at about 1.2 deaths per county-day.
However, the distribution shows a different picture, with 73% of county-days having zero deaths from COVID-19, and 86% showing less than two deaths. However, in the north, only 67% of days had zero deaths, vs. 77% of days in the south. Finally, two or more deaths occurred at 18% and 9% of the north and south county-days, respectively.
The exposure days for patients who died of the infection were set at 18-22 days before death, and the average minimum temperature was set at 42oF. However, it was about 33 oF and 49oF in the north and south, respectively.
The maximum temperature was, on average, 63.4°F, with 52°F and 70°F in the north and the south.
Ground-level ozone concentrations varied over an 8-hour exposure, and from north to south. The highest in the south and the north was 78 ppb and 61 ppb.
Significant Patterns
The researchers found a positive association between deaths and temperature minimum to be significant in the north, with a 5% increase in deaths at the county level with a 1°F increase in the five-day average of the minimum daily temperature. This could be due to increased contact rates rather than the temperature rise itself.
There was a significant negative association between lower ozone levels and higher COVID-19 death rates in the south, with a 2% fall in deaths at the county level with a rise of 1 ppb in the five-day average ozone level 18-22 days before. Ozone is a disinfectant that may inactivate the virus. Earlier studies showed a negative association with the number of COVID-19 cases and ozone levels, but the current is the first to demonstrate a robust relationship between COVID-19 mortality and ozone levels.
The study made use of mortality as the most reliable indicator of COVID-19 infection rates. It used American data to ensure the homogeneity of data due to single-nation sourcing. A fixed-effects model was used to control for confounding factors that vary across counties but remain constant in any given county over the study period, and thus prevent the misleading effect of factors that remain constant over time, such as the healthcare setup for the study period.
Day fixed-effects were also used to control for health interventions since these were constant across counties, even if they varied from day to day. The study also used a region-specific fixed-effects model to capture any mortality trend due to the disease, within a county, while controlling for policy changes in any state.
The results showed that minimum temperature changes had a robust impact by increasing mobility and contacts. This is seen only with spring, that is, in the March-May months of 2020. Spring tends to cause people to leave their homes more often, which may not be reflected during summer. More research will be needed to understand how these factors, especially ozone levels, and spring temperatures, affect the spread of the virus.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Article Revisions
- Mar 25 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
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