Table 7.
Relationship between incidence of coronaviruses and climatic variabilities.
| Study location | Study period | Study population | Infection type and Diagnostic test | Association with T | Association with RH | Other association | Statistical method | Author | Year |
|---|---|---|---|---|---|---|---|---|---|
| Guangzhou, China | January 2 to April 15, 2003 | laboratory-confirmed cases | SARS-CoV, clinical diagnosis | Tmax_7 (R = −0.438, P-value≤0.001) Tmin_7 (R = −0.193 P-value≤0.05) |
RH_7 (R = −0.271, P-value≤0.001) | P_7 (R = −0.361, P-value≤0.001) | The lag = 7, simple correlation | Jianguo Tan et al. (Tan et al., 2005) | 2004 |
| Beijing, China | March 5 to May 31, 2003 | laboratory-confirmed cases | SARS-CoV, clinical diagnosis | Tmax_7 (R = 0.528, P-value≤0.001) Tmin_7 (R = −0.475, P-value≤0.001) |
RH_7 (R = −0.448, P-value≤0.001) | P_7 (R= −0.513, P-value≤0.001) | The lag = 7, simple correlation | Jianguo Tan et al. (Tan et al., 2005) | 2004 |
| Taiyuan, China | March 7 to May 12, 2003 | laboratory-confirmed cases | SARS-CoV, clinical diagnosis | Tmax_7 (R = −0.310, p˂0.001) Tmin_7 (R = −0.214, NS) |
RH_7 (R = −0.321, P-value≤0.001) | P_7 (R = −0.488, P-value≤0.001) | The lag = 7, simple correlation | Jianguo Tan et al. (Tan et al., 2005) | 2004 |
| Hong Kong | February 15 to 31 May 2003 | laboratory-confirmed cases | SARS-CoV, clinical diagnosis | Tmax_7 = −0.453 Tmin_7 = −0.425 |
RH_7 (R = 0.067, NS) | P_7 (R = 0.364, P-value≤0.001) | The lag = 7, simple correlation | Jianguo Tan et al. (Tan et al., 2005) | 2004 |
| Hong Kong | 11 March to 22 May 2003 | hospital staff | SARS-CoV, clinical signs, chest X-ray, diagnostic tests in some patients and/or autopsy | An increase of 1 °C in air temperature was related to an average reduction of 0.7 staff patients. | – | – | regression analysis (odd ratio). | Kun Lin et al. (Lin et al., 2006) | 2005 |
| Beijing, China | April 3 to June 11, 2003 | laboratory-confirmed cases | clinical diagnosis | Temperature range (R = 0.337) Temperature (R = −0.718) |
Relative humidity (R = −0.784) | Wind velocity (R = 0.617), Barometric pressure (R = 0.210), Cloudiness (R = −0.569), and Precipitation (R = −0.379) |
Correlation | Jingsong Yuan et al. (Yuan et al., 2006) | 2006 |
| Hong Kong | April 21 to May 20, 2003 | laboratory-confirmed cases | SARS-CoV, clinical diagnosis | Tmax (R = −0.79), Tmin (R = −0.76) |
RH (R = 0.24) | (R = 0.57) | Pearson’s correlation | P. Bi et al. (Bi et al., 2007) | 2007 |
| Beijing, China | April 21 to May 20, 2003 | laboratory-confirmed cases | SARS-CoV, clinical diagnosis | Tmax (R = NS) Tmin (R = −0.41) |
RH (R = −0.5) | (R = NS) | Pearson’s correlation | P. Bi et al. (Bi et al., 2007) | 2007 |
| Worldwide | June 2012 to the Dec 2017. | Worldwide 2048 laboratory confirmed Cases |
MERS-CoV, clinical diagnosis | The highest global seasonal occurrence was found in the month of June, while the lowest was found in the month of January | – | – | M.S. Nassar et al. (Nassar et al., 2018) | 2018 | |
| Hubei Province, China | from January 23, 2020 to February 10, 2020. | SARS-CoV-2, clinical diagnosis | Tmean (R = −1.05 and P-value = 0.008) | – | Absolute Humidity (R = 0.761 and P-value = 0.048) | Loess regression and an exponential fit | Wei Luo et al. (Luo et al., 2020) | 2020 | |
| 31 provincial-level regions in mainland China | between Jan 20 and Feb 29, 2020 | the number of new confirmed and probable cases were obtained from 101 the China National Health Commission (CNHC) | SARS-CoV-2, clinical diagnosis | – | – | No significant association between COVID-19 incidence and absolute humidity | regression and smoothing scatterplot | Peng Shi et al. (Shi et al., 2020) | 2020 |
| Worldwide | COVID-19 Global Cases up to March 19, 2020 (13 and 7 countries with cold and warm climates. 4 countries considered as none | Worldwide laboratory confirmed Cases |
SARS-CoV-2, clinical diagnosis | Correlation between rate of spread and T (R = −0.72, P-value≤0.001) | Correlation between rate of spread and morning humidity (R = 0.2, P-value = 0.39) Correlation between rate of spread and evening humidity (R = 0.11, P-value = 0.65) |
Correlation between rate of spread and precipitation (R = −0.04, P-value = 0.87) Correlation between rate of spread and dew point (R = −0.62, P-value = 0.008) |
Pearson and Spearman correlation | Gil Caspi et al. (Caspi et al., 2020) | 2020 |