Several nations are currently experiencing a significant increase in coronavirus (COVID-19) cases, including Indonesia ( https://worldometers.info/coronavirus/). A total of 34,874,744 confirmed cases with 1,097,497 deaths (case fatality rate (CFR) 3.1%) were reported in 216 countries based on data from the World Health Organization ( https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200831-weekly-epi-update-3.pdf?sfvrsn=d7032a2a_4). In Indonesia, the number of people who have been infected and the number who have died are approximately 287,008 and 10,740 (CFR 3.7%), respectively, with the most predominant regions being Jakarta (73,700), East Java (43,536), and Central Java (22,440) ( https://covid19.go.id/peta-sebaran).

Based on various studies worldwide, the SARS-CoV-2 virus that is responsible for COVID-19 is described as highly contagious. Saliva droplets produced by asymptomatic carriers appear to be the possible transmission media. In addition, specific observations using highly sensitive laser beams indicated that loud speech tends to emit countless droplets of oral fluid per second. In a closed and stagnant air environment, the drops finally disappear from the viewing window within the range of eight to14 minutes. Based on these findings, regular speech shows a high probability of transmitting the airborne virus in confined spaces. ¹ Therefore, aerosol transfer appears to be the most significant method of SARS-CoV-2 spread compared with other media. ^{1 – 3} Furthermore, recent studies have shown that the virus remains active in airborne particles beyond three hours. ^{4 , 5}

Although related studies are minimal, the wind is perceived as a critical climatic factor for virus transmission. ⁶ Previous research studied four meteorological parameters (temperature, dew point, humidity, and wind speed). The number of coronavirus cases in Turkey demonstrated the function of wind speed in promoting the spread. The parameter with the highest correlation was generated by wind speed in 14 days and therefore showed that extensive wind speeds led to increased virus cases. ⁷

Conversely, higher wind speeds in external settings contribute to dilution and droplet removal, resulting in a decline in airborne concentration ( https://apps.who.int/iris/bitstream/handle/10665/70863/WHO_CDS_CSR_GAR_2003.11_eng.pdf?sequence=1&isAllowed=y). ⁸ Previous research from Brazil that examined the association between weather and COVID-19 spread in tropical climates countries showed that wind speed was negatively correlated (p < 0.01). Therefore, the variable also serves as a potential consideration in suppressing disease transmission. ⁹

Based on the description above, it can be assumed that wind speed is a major influencing factor of COVID-19 spread. Therefore, it was crucial to comprehend the effects of wind speed on the virus, as Jakarta appeared to be the pandemic's epicenter. Consequently, this research successfully investigated the relationship between wind speed and the weekly occurrence of COVID-19 in the Special Capital Region of Jakarta.

A step by step description of the protocols can be obtained at: dx.doi.org/10.17504/protocols.io.ewov1odzylr2/v1

The wind speed (maximum and mean) from March to September 2020 tended to fluctuate between 1.43 and 6.07 m/s. This variable appeared minimal during the last week of each month (fourth, fifth, fourth, fourth, and fifth weeks of March, April, May, June, and July, respectively). However, it showed a higher performance in the middle of each month (second, second, second, third, third, and third weeks of March, May, June, July, August, and September, respectively).

Furthermore, the maximum and minimum wind speed values of 6.07 and 4.5m/s occurred during the first, ninth, and 15 ^th weeks, respectively. Meanwhile, the optimal and minimum average wind speeds of 2.75 and 1.43 m/s were obtained in the 29 ^th and fourth weeks, respectively.

Based on the correlation analysis between the average wind speed and COVID-19 cases in Jakarta, a significant correction between strong and unidirectional associations was reported, indicating that higher average wind speeds accelerated the virus transmission. This outcome matched several previous studies, ^{7 , 11 – 16} where the wind speed was also known to increase the airborne SARS-CoV-2 spread. ¹² Droplets released during normal speech tend to survive in the air between eight and 14 minutes, similar to confined environments. ¹ Recent studies have also shown that the virus can remain infectious in airborne particles beyond three hours. ^{4 , 5} Therefore, aerosol transmission appears to be the main channel, compared with other media. ^{1 – 3} Under these circumstances, the wind speed variable plays a significant role in promoting the spread, ⁷ and with wind speeds in Jakarta ranging from 1.43 to 6.07 m/s, the surviving airborne virus quickly spreads. ¹²

In this context, higher wind speeds adversely impact individuals who do not correctly apply health protocols (avoiding crowds, not keeping close distances, and not wearing/removing masks). ⁷ Therefore, the transmission of impure cases is influenced by the rate of wind speed spreading the virus. Furthermore, government policies also play an essential role in influencing the disease rates, in the form of implementing health protocols (washing hands, ¹⁷ wearing masks, ¹⁷ physical distancing ¹⁸ ), staying at home, ¹⁹ working from home, ^{20 , 21} and large-scale social restrictions/enforcement of restrictions on community activities (Pembatasan Sosial Berskala Besar/Pemberlakuan Pembatasan Kegiatan Masyarakat). ^{22 – 24}

Based on a weekly graphical analysis of Jakarta, the fluctuations in wind speed tended towards the pattern of COVID-19 cases. The variable results were also consistent with similar outcomes of the correlation test in Jakarta, indicating a significant relationship with strong and positive patterns. This also indicated that higher average wind speeds triggered extensive COVID-19 spread.

The spatial relationship between wind speed and COVID-19 cases in Jakarta from March to September 2020 showed that urban villages that had high wind speeds tended to experience a faster transmission than other areas with medium and low values. However, a smaller number of villages with moderate and low wind speeds also showed increased cases. This result was possibly influenced by determining the source location of the COVID-19 cases using the domicile/residential address in the last 14 days, despite the possible occurrence of the infection while conducting external activities. Therefore, the spatial pattern of COVID-19 cases in Jakarta did not match the actual spatial pattern from the infection origin. ²⁵ In addition, other factors, including community non-compliance in implementing health protocols and Pembatasan Sosial Berskala Besar (PSBB) or large-scale social restrictions policies, led to transmissions outside the home ( https://www.liputan6.com/news/read/4368373/survei-bps-55-persen-masyarakattak-patuhi-protokol-kesehatan-karena-tidak-ada-sanksi). The previous survey proved that approximately 26.46% of the community did not correctly implement health protocols outside the home ( https://www.bps.go.id/publication/2020/09/28/f376dc33cfcdeec4a514f09c/perilaku-masyarakat-di-masa-pandemi-covid-19.html). Therefore, strict health protocols (washing hands, wearing masks, physical distancing), implementation of maximum capacity, and operating hours rules in places with open-air conditions and crowds, particularly tourist attractions in areas with high wind speeds, including coastal areas, are among several considerations for policymakers.

The majority of the previous studies employed case and wind speed data on similar days, although the reporting record did not represent the infection date, as the symptoms typically manifested after days of transmission. The time required for tracking and testing was equally essential, causing difficulty in determining the actual infection date. Therefore, to minimize possible bias, daily case and wind speed data were converted to a weekly form, based on a mean incubation period (symptom appearance) of between five and six days, with a maximum of 14 days. ²⁵

This study is expected to consider certain limitations that may have influenced the overall results. No analysis was conducted using time lags, and, therefore, it was not possible to determine the most significant relationship between the wind speed and the COVID-19 case variables between week one (t) and subsequent intervals ((t+1), (t+2), and so on). In addition, the unavailability of variable data in smaller regions, neighborhood/community associations (Rukun Tetangga/Rukun Warga), produced indefinite distribution patterns. However, other risk factors, including population size, density, mobility and immunity, community behavior (washing hands, wearing masks, and physical distancing), and the nature of the virus were not included in this research. In addition, the limited period of data collection (seven months) possibly influenced the analysis. Furthermore, a comparative analysis of the relationship between wind speed variables and case variables was performed per week, every 14 days, and monthly, indicating that the time frames were closely related. Therefore, further studies are expected to consider the abovementioned factors and generate significant improvements. Low wind speeds are associated with a high concentration of air pollutants, and therefore may promote a longer permanence of viral particles in polluted air of cities, thus favoring an indirect means of diffusion of the novel coronavirus (SARS-CoV-2). ²⁶ Since this research did not include concentration of pollutants, therefore, it is suggested that future research should involve pollution levels in the area of the study to achieve comprehensive results.

Based on the overall results, environments with high average wind speeds tend to demonstrate an increased number of COVID-19 cases, particularly in coastal regions. This factor also accelerates airborne SARS-CoV-2 spread among people that do not correctly apply the prescribed health protocols. Therefore, the impure cases are triggered by the rate of the wind-speed-based transmission. Consequently, strict health protocols (washing hands, wearing masks, physical distancing), applying maximum capacity, and regulating work hours in places with open-air conditions and crowd potentials, especially tourist attractions in areas with high wind speeds, including coastal regions, serve as a basis for consideration in policymaking.

This research was approved by the Research and Community Engagement Ethical Committee, Faculty of Public Health, Universitas Indonesia, No. 210/UN2.F10. D11/PPM.00.02/2021.