PMC:7229913 / 5909-13416 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/7229913","sourcedb":"PMC","sourceid":"7229913","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7229913","text":"3 Results and discussion\nThe global probability distribution of COVID-19 cases with respect to the ambient temperature is shown in Fig. 1 . The temperature interval at each panel is 1 °C. The results clearly illustrate that 60.0% of the confirmed COVID-19 cases were found in places where the air temperature ranged from 5 °C to 15 °C, with a peak at 11 °C. However, there were few confirmed cases located at cold (lower that 0 °C) and hot (greater than 30 °C) regions. Fitting the results using normal distribution, we found that the mean and the standard deviation of the fitted normal distribution curve were 11.54 °C and 5.47 °C, respectively. A previous study analyzed the relationship between daily confirmed COVID-19 cases and air temperature from 122 cities in China (Xie and Zhu, 2020) and pointed out that confirmed COVID-19 cases increased by 4.861%/°C for ambient temperature lower than 3 °C. Based on the analysis of global COVID-19 cases, our results demonstrated that confirmed COVID-19 cases increased by 27,536 cases/°C for ambient temperature lower than 10 °C. Thus, the rate of increase in COVID-19 cases induced by temperature may have been underestimated by the previous study.\nFig. 1 Relationship of daily confirmed cases of coronavirus disease 2019 with (a) corresponding temperatures, (b) daily temperature difference, (c) maximum temperature, and (d) minimum temperature globally from January 22, 2020 to May 6, 2020. The blue line represents the fitted normal distribution curve. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nTo understand the impact of ambient temperature on dispersal of global COVID-19 pandemic in a better way, we investigated the relationship between daily confirmed cases and maximum/minimum temperatures. It was observed that most of the daily COVID-19 cases were located in regions with maximum temperature range of 5 °C to 30 °C. A similar study by Triplett (2020) indicated that the rate of confirmed COVID-19 cases will be significantly reduced when maximum temperature reaches above 22.5 °C. Moreover, the cases were mainly concentrated in regions with minimum temperature range of 0 °C to 15 °C. It is well known that large daily temperature difference may easily trigger influenza. Therefore, we investigated the relationship between daily confirmed cases and temperature difference. The results showed that rapid increase in the number of COVID-19 cases was associated with a daily temperature difference threshold of 8 °C and the number of cases decreased when daily temperature difference was greater than 8 °C. These results indicated that there was a nonlinear association between confirmed cases of COVID-19 and daily temperature difference.\nThere was an obvious relationship between the number of confirmed cases and relative humidity, with a peak at 65% (Fig. 2 ). The distribution was much broader (30% to 100%) when compared with distribution of COVID-19 cases according to temperature. Additionally, we analyzed the variation in the number of confirmed COVID-19 cases according to absolute humidity. Approximately 73.8% of the cases were concentrated in regions with absolute humidity ranging from 3 g/m3 to 10 g/m3, with a peak at 5 g/m3. This result suggests that humid conditions were conducive for the spread of the COVID-19 pandemic.\nFig. 2 Relationship of daily confirmed cases of coronavirus disease 2019 with (left) daily relative humidity and (right) absolute humidity. The blue line represents the fitted normal distribution curve. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nFig. 3 presents the time-series zonal distribution of daily COVID-19 cases and their dispersal trend. As shown in Fig. 3(a), the temperature zone (5 °C–15 °C) and the center of the fitted normal distribution curve of the zonal mean daily cumulative COVID-19 cases were coincident. The center of the zone denoting COVID-19 cases moved toward higher latitude along with the temperature zone. Notably, there was a breakpoint on March 14, 2020 due to the outbreak of COVID-19 in Europe. As a result, the center of the zone denoting COVID-19 cases switched to 42.39°N and its standard deviation became much smaller. Clearly, most of the cases (68.2%) of COVID-19 occurred at higher latitudes, spreading along a path where the temperature ranged from 5 °C to 15 °C. This finding confirms that air temperature truly affects the distribution of COVID-19. It is noteworthy that the COVID-19 pandemic has not spread to areas with high population densities. Hence, we predict that the center of the fitted normal distribution curve of zonal mean COVID-19 cases will continually move to higher latitudes along the temperature zone between 5 °C to 15 °C over time. Therefore, the scale of the COVID-19 pandemic will be substantially reduced in early May and might recur in large mid-latitude cities in autumn 2020. It is very important to pay more attention to places at higher latitudes. In addition, mid-latitude locations with higher population densities will also face the possibility of another COVID-19 outbreak in the autumn.\nFig. 3 (a) Relationship between cumulative cases of coronavirus disease 2019 (COVID-19) and temperatures from January 22, 2020 to May 6, 2020.\nThe orange zone represents the latitudinal zone with a mean surface temperature between 5 °C and 15 °C in 2019 according to a reanalysis of the National Centers for Environmental Prediction data. Blue lines (red points) represent the standard derivation (center) of the fitted normal distribution curve of zonal mean cumulative COVID-19 cases each day. The illustration is an example of the normal distribution fitted on March 13, 2020. Notably, daily COVID-19 cases in several countries such as China, the United States, and Canada were counted separately for each province. (b) Zonal mean of the gridded populations from 1980 to 2010 developed by the Center for Global Environmental Research at the National Institute for Environmental Studies, Japan. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)\nOur findings suggest that there is an optimal climatic zone in which the concentration of SARS-CoV-2 markedly increases in the ambient environment (including the surfaces of objects). Even though the dispersal of the COVID-19 outbreak is affected by many countermeasures and medical conditions, our results confirm that there is an optimal temperature zone for the survival of SARS-CoV-2. The concentration of SARS-CoV-2 can markedly increase in the ambient environment including the surfaces of objects in this temperature range. It is worth recognizing that the spread of the COVID-19 outbreak is affected by several factors. In the present study, we investigated the natural factors affecting the COVID-19 pandemic. The analysis of large datasets (samples) yielded significant results with a high degree of confidence in the findings. These findings are important for the prediction of COVID-19 transmission in the near future. We cannot rely on the conjecture that COVID-19 outbreak will stop with increase in the temperature in summer. Undoubtedly, control strategies including school closure and social distancing have reduced the number of total cases considerably (Prem et al., 2020; Luo et al., 2020; Kissler et al., 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