Browsing UMB Coronavirus Publications by Subject "Temperature"
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How fever is defined in COVID-19 publications: A disturbing lack of precisionFever is the single most frequently reported manifestation of COVID-19 and is a critical element of screening persons for COVID-19. The meaning of "fever"varies depending on the cutoff temperature used, the type of thermometer, the time of the day, the site of measurements, and the person's gender and race. The absence of a universally accepted definition for fever has been especially problematic during the current COVID-19 pandemic. This investigation determined the extent to which fever is defined in COVID-19 publications, with special attention to those associated with pregnancy. Of 53 publications identified in which "fever"is reported as a manifestation of COVID-19 illness, none described the method used to measure patient's temperatures. Only 10 (19%) publications specified the minimum temperature used to define a fever with values that varied from a 37.3 °C (99.1 °F) to 38.1 °C (100.6 °F). There is a disturbing lack of precision in defining fever in COVID-19 publications. Given the many factors influencing temperature measurements in humans, there can never be a single, universally accepted temperature cut-off defining a fever. This clinical reality should not prevent precision in reporting fever. To achieve the precision and improve scientific and clinical communication, when fever is reported in clinical investigations, at a minimum the cut-off temperature used in determining the presence of fever, the anatomical site at which temperatures are taken, and the instrument used to measure temperatures should each be described. In the absence of such information, what is meant by the term "fever"is uncertain.
Inverse correlation between average monthly high temperatures and COVID-19-related death rates in different geographical areasBackground With the aim of providing a dynamic evaluation of the effects of basic environmental parameters on COVID-19-related death rate, we assessed the correlation between average monthly high temperatures and population density, with death/rate (monthly number of deaths/1 M people) for the months of March (start of the analysis and beginning of local epidemic in most of the Western World, except in Italy where it started in February) and April 2020 (continuation of the epidemic). Different geographical areas of the Northern Hemisphere in the United States and in Europe were selected in order to provide a wide range among the different parameters. The death rates were gathered from an available dataset. As a further control, we also included latitude, as a proxy for temperature. Methods Utilizing a publicly available dataset, we retrieved data for the months of March and April 2020 for 25 areas in Europe and in the US. We computed the monthly number of deaths/1 M people of confirmed COVID-19 cases and calculated the average monthly high temperatures and population density for all these areas. We determined the correlation between number of deaths/1 M people and the average monthly high temperatures, the latitude and the population density. Results We divided our analysis in two parts: analysis of the correlation among the different variables in the month of March and subsequent analysis in the month of April. The differences were then evaluated. In the month of March there was no statistical correlation between average monthly high temperatures of the considered geographical areas and number of deaths/1 M people. However, a statistically significant inverse correlation became significant in the month of April between average monthly high temperatures (p = 0.0043) and latitude (p = 0.0253) with number of deaths/1 M people. We also observed a statistically significant correlation between population density and number of deaths/1 M people both in the month of March (p = 0.0297) and in the month of April (p = 0.0116), when three areas extremely populated (NYC, Los Angeles and Washington DC) were included in the calculation. Once these three areas were removed, the correlation was not statistically significant (p = 0.1695 in the month of March, and p = 0.7076 in the month of April). Conclusions The number of COVID-19-related deaths/1 M people was essentially the same during the month of March for all the geographical areas considered, indicating essentially that the infection was circulating quite uniformly except for Lombardy, Italy, where it started earlier. Lockdown measures were implemented between the end of March and beginning of April, except for Italy which started March 9th. We observed a strong, statistically significant inverse correlation between average monthly high temperatures with the number of deaths/1 M people. We confirmed the data by analyzing the correlation with the latitude, which can be considered a proxy for high temperature. Previous studies indicated a negative effect of high climate temperatures on Sars-COV-2 spreading. Our data indicate that social distancing measure are more successful in the presence of higher average monthly temperatures in reducing COVID-19-related death rate, and a high level of population density seems to negatively impact the effect of lockdown measures.