The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Will Coronavirus Pandemic Diminish by Summer?
Open accessAbstract
The novel coronavirus (2019-nCoV) has spread rapidly to multiple countries and has been declared a pandemic by the World Health Organization. While influenza virus has been shown to be affected by weather, it is unknown if COVID19 is similarly affected. In this work, we analyze the patterns in local weather of the regions affected by 2019-nCoV virus until March 22, 2020. So far, 83% of testing have been conducted in non-tropical countries (30N and above) and 90% of the 2019-nCoV cases have been recorded in the same countries within a temperature range of 3 to 17C. Similarly, ~72% of the measurements were done in countries with humidity between 3 and 9g/m3 and 90% of the cases were observed within the same range of absolute humidity (AH). The higher number of tests and global connectivity of the northern-cooler countries may explain the difference in number of confirmed 2019-nCoV cases between cooler and warmer-humid regions. Nonetheless, several countries between 30N and 30S such as Australia, UAE, Qatar, Singapore, Bahrain, Qatar and Taiwan have performed extensive testing per capita and the number of positive 2019-nCoV cases per capita are lower in these countries compared to several European countries and the US. Therefore, even though currently available data is skewed by minimal testing per capita in many tropical countries, it is possible that weather plays a role in the spread of 2019-nCoV which warrants an investigation. In the last 10 days, thousands of new cases have been documented in regions with T >18C suggesting that the role of warmer temperature in slowing the spread of the 2019-nCoV, as suggested earlier might only be observed, if at all, at much higher temperatures. Unlike temperature, however, the range of AH across which most of the cases have been documented has consistently been between 3 and 9g/m3. Current data, although limited, suggests that it is extremely unlikely that the spread of 2019-nCoV would slow down in the USA or Europe, due to environmental factors, because a large number of cases have already been reported in the range of AH and T experienced by these regions for most part of the year. Given previous associations between viral transmission and humidity and the range of AH across which the majority of the 2019-nCoV cases have been observed till date, the role of absolute humidity merits further investigation with laboratory experiments studying the sensitivity of 2019-nCoV across a range of temperature and humidity conditions. On the other hand, if, new cases in April and May continue to cluster within the current observed range of AH i.e. 3 to 9g/m3, then the countries experiencing monsoon, i.e. having high absolute humidity (>10 g/m3) could see a slowdown in transmissions, due to climatic factors. The data analyzed here are rapidly changing and with several unknowns including how the virus is mutating and evolving, what are the reproductive numbers and the dominant way of spreading. If 2019-nCOV is indeed sensitive to environmental factors, then it could be used to optimize the 2019-nCoV mitigation strategies. Our results in no way suggest that 2019-nCoV would not spread in warm humid regions and effective public health interventions should be implemented across the world to slow down the transmission of 2019-nCoV.
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Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1
van Doremalen, N., Bushmaker, T., Morris, D. H., Holbrook, M. G., Gamble, A., Williamson, B. N., Tamin, A., Harcourt, J. L., Thornburg, N. J., Gerber, S. I., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2004973 · Cited by 9,951
Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle
Lu, H., Stratton, C. W., & Tang, Y. (2020) · Journal of Medical Virology · doi:10.1002/jmv.25678 · Cited by 3,504
Coronavirus envelope protein: current knowledge
Schoeman, D., & Fielding, B. C. (2019) · Virology Journal · doi:10.1186/s12985-019-1182-0 · Cited by 2,074
Identification of a new human coronavirus
van der Hoek, L., Pyrc, K., Jebbink, M. F., Vermeulen-Oost, W., Berkhout, R. J. M., Wolthers, K. C., Wertheim-van Dillen, P. M. E., Kaandorp, J., Spaargaren, J., & Berkhout, B. (2004) · Nature Medicine · doi:10.1038/nm1024 · Cited by 1,886
The Computation of Equivalent Potential Temperature
Bolton, D. (1980) · Monthly Weather Review · doi:10.1175/1520-0493(1980)108<1046:tcoept>2.0.co;2 · Cited by 1,691
Influenza Virus Transmission Is Dependent on Relative Humidity and Temperature
Lowen, A. C., Mubareka, S., Steel, J., & Palese, P. (2007) · PLoS Pathogens · doi:10.1371/journal.ppat.0030151 · Cited by 1,669
Long Short Term Memory Networks for Anomaly Detection in Time Series.
Malhotra, P., Vig, L., Shroff, G. M., & Agarwal, P. (2015) · The European Symposium on Artificial Neural Networks · Cited by 1,259
Coronavirus Pathogenesis and the Emerging Pathogen Severe Acute Respiratory Syndrome Coronavirus
Weiss, S. R., & Navas-Martin, S. (2005) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.69.4.635-664.2005 · Cited by 1,256
Metadata
- Authors
- Bukhari, Q., & Jameel, Y.
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2020
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W3013328394
- Cited by
- 268
- References
- 19
- Type
- posted content
- Language
- en
- Open access
- green
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