Impact of Climate Variables on COVID-19 Pandemic in Asia: A Systematic Review

COVID-19 has become a global pandemic and threatens public health systems worldwide. Virus transmission can be influenced by several factors, one of which is climatic conditions. Temperature, humidity, precipitation, wind speed, and solar radiation play an important role in the transmission of infectious diseases and are variables that can determine the resistance of the SARS virus. This paper aimed to critically assess and provide evidence-based on the impact of climate variables on COVID-19 cases in Asia based on current knowledge to form the basis of guidelines for health care and prevention efforts. This systematic review used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The articles were searched from ProQuest, Scopus, PubMed, and Springerlink databases. The reviewers had screened 2.784 abstracts, 103 full-text publications, and ultimately included 11 systematic reviews. The review found a consistently positive relationship between climate variables and COVID-19. Average temperature, maximum temperature, minimum temperature, and humidity (r = 0.83, 0.94, 0.93, 0.30) were significantly correlated with COVID-19 cases. Temperature, maximum humidity, and population density (adjusted R2 = 0.53, p<0.05), can be used as references in planning interventions during potential future pandemics. Linear regression framework, high humidity, and high temperature (p<0.05) significantly reduce the transmission of COVID-19. This systematic review shows that climate plays a role in the spread of the COVID-19 pandemic in Asia.


Introduction
Coronavirus Disease 2019 (COVID-19) has become a worldwide pandemic and threatens public health systems worldwide. There are many dynamics regarding the causative agent of COVID-19. Currently, SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) was determined to be the cause. 1 The COVID-19 is currently the third disease caused by the coronavirus transmitted from animals to humans. It was identified as a zoonotic coronavirus, similar to the SARS-CoV (Severe Acute Respiratory Syndrome Coronavirus) and MERS-CoV (the Middle East Respiratory Syndrome Coronavirus), which results in a severe respiratory syndrome after twenty years. 2,3 As of August 31, 2020, a total of 24,854,140 confirmed cases were reported worldwide, with 838,924 deaths (CFR 3.4%) with cases reported in 216 countries/regions. 4 Experts believe in the influence of seasons on viral epidemiology. Low temperature is the most optimal condition for viruses such as a respiratory syncytial virus (RSV), influenza virus, and human metapneumovirus (hMPV) to cause infection in humans. This season causes RSV and influenza cases to increase in winter, while hMPV cases occur most of the year and peak in winter and spring. 5 The significant increase in the incidence of influenza at low temperatures and high humidity points to the potential impact of climatic conditions on the distribution and transmission of COVID-19, amid consideration of other non-climatic factors. [6][7][8][9] Climatic conditions are the essential factors that affect COVID-19 because they can be a direct cause of biological interactions between agents and humans. Climatic elements such as temperature, humidity, rainfall, wind speed, and sunlight are significant factors in disease transmission and are parameters that can determine the survival of the SARS virus. [10][11][12] Therefore, this systematic review aimed to critically assess and provide evidence-based on the impact of climate variables on COVID-19 cases in Asia based on current knowledge to form the basis of guidelines for health care and preven-tion efforts.

Search Strategy
For this review, articles were sourced from four science databases; ProQuest, Scopus, Pubmed, and Springerlink. The systematic review was adjusted using the PRISMA guidelines. 13 The searching process utilized two main keywords, which include climate and COVID-19. The population was people diagnosed with COVID-19. The comparison was countries, study characteristics, climate variables, the outcome was COVID-19, and the type of research using qualitative methods.
The search strategy in ProQuest: climate AND covid-19 as keywords. Full text, peer review, the source is an academic journal, date of publication last 12 months, English language are included in the filter. In Scopus: TITLE-ABS-KEY climate AND covid-19 AND (LIMIT-TO (ACCESSTYPE(OA))) AND (LIMIT-TO(PUBYEAR,2020)) AND (LIMIT-TO(DOCTYPE, "ar")). In Pubmed: (("climate"[All Fields]) AND ("covid-19"[All Fields]). Full text, type of article is a journal article, date of publication last one year, English language are included in the filter. The search strategy in Springerlink: climate AND covid-19 as a keyword.

Inclusion and Exclusion Criteria
All original articles in English, academic or research articles, ecological and time-series research, and the articles looking at the correlation between climate (temperature, humidity, precipitation, wind speed, and sunlight) and COVID-19 cases were included.
The study about the relationship between climate and COVID-19 recovery rates, COVID-19 reproduction rates, and variables related to COVID-19 in addition to the number of cases, review articles, case reports, outbreak reports, and qualitative method were excluded.

Study Selection
Three reviewers selected the research based on the eligibility of the articles to be reviewed from the title, abstract, and full text. Three reviewers were selecting the articles based on their area of expertise.

Data Extraction
Data taken based on the conditions met, among others, the author, the study period, the year of publication, the country carried out, the research design and research method, the research area, and the correlation between climate (temperature, humidity, precipitation, wind speed, and sunlight), and COVID-19 cases.

Data Synthesis
Data synthesis was carried out using narrative synthesis. The research area included countries in the Asian continent. The variables of climate reviewed were based on the local state meteorological and climatological agency. The number of COVID-19 cases was reviewed based on the diagnosis of COVID-19 cases recorded at the local state health department. To reduce the risk of bias, the three reviewers worked independently. It would be done through an online discussion process and reading all the selected articles if they have different opinions. The eligible articles were then analyzed qualitatively based on the five variables: temperature, humidity, precipitation, wind speed, and sunlight exposure. The review used a PRISMA guideline; a checklist has been carried out using the PRISMA Checklist 2020.

Results
The studies included in this review were 11 articles. From 11 studies, three studies were from India, two studies were from Turkey and Japan, and Bangladesh, Indonesia, Iran, China, and Gulf Countries each. The results were resumed in Table   1. Based on studies reviewed, temperature (average, minimum, maximum, ambient), humidity, wind speed, average precipitation, number of sunny days with COVID-19. The Average temperature was at 2 m (r = 0.83), maximum tempera-

Temperature
In the studies reviewed, the temperature was significantly associated with the incidence of daily COVID-19 with and without time lag. Therefore, it was concluded that temperature drives the spatial and temporal correlation of the COVID-19 outbreak in China. It should be considered the optimal climate predictor for the incidence of COVID-19. 25 Several flu viruses that occur in northern states are caused by flu viruses of the same family type. This flu has a cyclic pattern of events known as "flu season." The flu virus was widespread during fall and winter and reached its peak between December and May. 26 Worldwide, cases of human morbidity and mortality from COVID-19 continue to increase in the "flu season," but COVID-19 was not the flu. Data obtained from the China National Meteorological Center and the Hong Kong Observatory, China, shows that the COVID-19 outbreak occurred during winter, similar to the previous SARS epidemic outbreak. 9 Research conducted in 122 cities in China found a significant relationship between average temperature and the number of positive cases of COVID-19. 27 Also, the relationship between temperature and COVID-19 covering all countries affected by COVID-19, showed the result of an increase in daily temperature by an average of one degree Fahrenheit reduced the number of cases by about 6.4 cases/day. There is a negative correlation between the average temperature per country and the number of SARS-CoV-2 infection cases. This association remains strong even incorporating additional variables and controls (maximum temperature, average temperature, minimum temperature, and precipitation) and fixed state effects. 10 The study explained that temperature was significantly associated with daily COVID-19 incidence with and without lag time. In addition, the researchers also found that the rate of transmission decreased as the temperature increased and that the increase in temperature contributed to a further decrease in infection rates and outbreak size. Therefore, it is concluded that temperature drives the spatial and temporal correlation of the COVID-19 outbreak in China and should be considered as the optimal climate predictor for the incidence of COVID-19. 25 A research conducted by Bashir et al. (2020) in New York, USA, confirms that there are significant results between the mean temperature and the total cases and deaths from COVID-19. 28 Humidity High humidity, associated with low temperature, is an essential factor in influenza virus transmission, either by maintaining virulence or weakening the host by cooling the body or drying out the respiratory tract. 29 The literature shows that SARS-CoV transmission is similar to the influenza virus in terms of climate fluctuations. 30 The relationship between humidity and COVID-19 cases can be proven by the research conducted by Liu et al. (2020) in 30 provincial capitals in China that show a statistically significant relationship between absolute humidity and the number of COVID-19 cases. In addition, the association increased with the accumulated time duration up to 14 days. The study concluded that meteorological factors, particularly absolute humidity, played an independent role in the transmission of COVID-19 after controlling for population migration. Local weather conditions with low temperatures, mild diurnal temperature ranges, and low humidity tend to favor transmission. 31 A similar study was conducted by Oliveiros et al. (2020) in 31 provinces in Mainland China, whose results show that humidity has a negative correlation with the doubling time of COVID-19 cases. This result means that, when humidity is low, the doubling time of COVID-19 cases will be longer, so the rate of progression of COVID-19 is expected to be slower. However, humidity and temperature variables only contributed up to a maximum of 18% of the variation.
In comparison, the remaining 82% was related to other factors such as controlling population mobilization, public health policies, population density, transportation, and cultural aspects. 8 Precipitation Precipitation was one of the climatic factors which seem to be an essential factor to consider. Based on research conducted by Sobral et al. (2020), covering all countries affected by COVID-19 showed a positive correlation between precipitation and transmission of SARS-CoV-2.
Countries with higher rainfall measurements show an increase in disease transmission. For every inch of increase in mean/day rainfall, there was an increase of 56.01 cases/day. 10 In contrast to research conducted by Menebo (2020) which examined the relationship between temperature and precipitation with daily new cases of COVID-19 in Norway, it was shown that among the seven weather variables studied, maximum temperature and the normal 87 temperature had a positive and significant correlation with COVID-19. On the other hand, the rainfall measured at 7.00 a.m. has a negative and significant correlation with COVID-19, which means that the higher the rainfall, the lower the cases of COVID-19. Various arguments can be given for the negative relationship between rainfall and new cases. One of them was the hypothesis that people will avoid going out if it rains. On the other hand, people are more prone to breaking the 'stay at home' rule when the sun is shining outside, thus becoming exposed to the virus. 32

Wind Speed
The wind was implied as a critical climatic factor for the transmission of COVID-19. However, studies on this factor were still minimal. 33 Based on research conducted by Rosario et al. (2020), who conducted a study on the relationship between weather and COVID-19 cases in tropical countries showed that wind speed had a negative correlation (p<0.01). Therefore, high temperatures and wind speed were potential factors to reduce the spread of COVID-19. 34 Research conducted by Coşkun et al. (2020) has had a different result. Research conducted by collecting climate values (temperature, humidity, number of sunny days, wind intensity) from 81 provinces in Turkey in March 2020 shows that population density and wind effectively spread the virus. These two factors explain 94%of the variance in the spreading virus. In addition, population density mediates the effect of wind speed (9%) on the number of COVID-19 cases. The finding that the invisible COVID-19 virus in the air spreads more in windy weather suggests that airborne viruses threaten humans with wind speeds that increase air circulation. 16

Sunlight Exposure
The results of research conducted by Rosario et al. (2020) in Rio de Janeiro, Brazil, showed a strong negative correlation between solar radiation and the incidence of COVID-19 (r = 0.609, p < 0.01). This result means that high solar radiation can reduce the incidence of COVID-19. 34 This research is in line with the study conducted by Ratnesar-Sumate et al. (2020), who proved that sunlight could kill SARS-CoV-2 on the surface. This study also demonstrated the effectiveness of natural sunlight as a disinfectant for contaminated non-permeable surfaces. 11 Based on research conducted by Asyary and Veruswati (2020), it was found that a higher duration of sunlight exposure was also associated with more case recovery from COVID-19 in patients. Sunlight can maintain the health condition of COVID-19 patients so that they have a chance to recover. Sunlight boosted the immune system, which slows down the development of influenza and SARS agents in the human body. 35,36

Limitations
This systematic review had some limitations. There were only 11 articles that met the inclusion criteria, and most of the articles did not examine the climate element thoroughly, thus affecting the results of the analysis. Due to the lack of controlled studies, a meta-analysis was not performed. This study could only see the relationship/ correlation and did not analyze the causal relationship.
In addition, this study used secondary data so that the level of bias is less controllable.

Conclusion
This systematic review found a positive association between temperature (average, minimum, maximum, ambient), humidity, wind speed, average precipitation, number of sunny days with COVID-19. This systematic review shows that climate plays a role in the spread of the COVID-19 pandemic in Asia. The results of this review might be used as a reference for researchers to conduct further research. In addition, it can also be used as input for policymakers as a reference for the preparation of the COVID-19 pandemic prevention program.