key: cord-0946295-11pcdnlw
authors: Sethwala, A.; Akbarally, M.; Better, N.; Lefkovits, J.; Grigg, L.; Akbarally, H.
title: The effect of ambient temperature on worldwide COVID-19 cases and deaths - an epidemiological study
date: 2020-05-18
journal: nan
DOI: 10.1101/2020.05.15.20102798
sha: 9082bff2bab68c199d1ce43d6cfdfc4abe8179fb
doc_id: 946295
cord_uid: 11pcdnlw

Background The role of ambient temperature in the spread of SARS-CoV-2 infections and subsequent deaths due to COVID-19 remains contentious. Coronaviruses such as the 2003 SARS-CoV showed an increased risk of transmission during cooler days. We sought to analyse the effects of ambient temperature on SARS-COV-2 transmission and deaths related to the virus. Methods The world population of COVID-19 cases and attributable deaths from the 23rd January 2020 to 11th April 2020 were analysed. Temperature 5 days before cases and 23 days prior to deaths (to account for the time lag of incubation period and time from symptoms to death) was compared to the average temperature experienced by the world population. Results The total number of cases during this period was 1,605,788 and total number of deaths was 103,471. The median temperature at the time of COVID-19 infection was 9.12C (10-90th percentile 4.29-17.97C) whilst the median temperature of the world population for the same period was 9.61C warmer at 18.73C (10-90th percentile 4.09-28.49C) with a notional p-value = 5.1 x10-11. The median temperature at the time of a COVID-19 death was 9.72C (10-90th percentile 5.39-14.11C) whilst the median temperature of the world population was 7.55C warmer at 17.27C (10-90th percentile 2.57C-27.76C) with a notional p-value = 1.1 x10-10. 80% of all COVID-19 related cases and deaths occurred between 4.29C and 17.97C. Conclusion A definitive association between infection rate and death from COVID-19 and ambient temperature exists, with the highest risk occurring around 9C. Governments should maintain vigilance with containment strategies when the ambient temperatures correspond to this highest risk.

The role of ambient temperature in the spread of SARS-CoV-2 infections and subsequent deaths due to COVID-19 remains contentious. Coronaviruses such as the 2003 SARS-CoV showed an increased risk of transmission during cooler days. We sought to analyse the effects of ambient temperature on SARS-COV-2 transmission and deaths related to the virus.

The world population of COVID-19 cases and attributable deaths from the 23 rd January 2020 to 11 th April 2020 were analysed. Temperature 5 days before cases and 23 days prior to deaths (to account for the time lag of incubation period and time from symptoms to death) was compared to the average temperature experienced by the world population.

The total number of cases during this period was 1,605,788 and total number of deaths was 103,471. The median temperature at the time of COVID-19 infection was 9.12°C (10-90 th percentile 4.29-17.97°C) whilst the median temperature of the world population for the same period was 9.61°C warmer at 18.73°C (10-90 th percentile 4.09-28.49°C) with a notional pvalue = 5.1 x10 -11 . The median temperature at the time of a COVID-19 death was 9.72°C (10- -Whilst laboratory studies and epidemiological data on other coronaviruses have shown a link between cooler temperatures and higher rates of coronavirus transmission, a putative association between temperature and SARS-CoV-2 infection rates was yet to be convincingly established.

-Our results show a clear association between the rates of infection and death from COVID-19 and ambient temperature, with the highest risk occurring around 9°C.

-These findings provide strong support for the role of ambient temperature in determining where and when significant outbreaks of COVID-19 infection occur.

-This information may be vital for governments and public health authorities when determining their policies for containment, mitigation and surveillance of COVID-19 outbreaks; for example, a strategy to relax measures such as social distancing may be best avoided at times when ambient temperatures correspond to the highest risk of transmission.

. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) Introduction SARS-CoV-2 is the causative pathogen for COVID-19 and was first identified in December 2019 after a series of cases of pneumonia were linked to a live animal and seafood market in Wuhan, China. 1 It soon spread rampantly throughout the world resulting in a pandemic that has infected over 1.7 million people and led to over 100,000 deaths as of 12 th April 2020. 2 While South East Asia may have been expected to be the region most affected due to its geographical proximity and travel relationship with Wuhan, it has been cooler, further Experiments on coronaviruses in controlled environments show that conditions conducive to its survival are at temperatures around 4°C and relative humidity between 20-80%. 3 In these conditions, coronaviruses can survive up to 28 days. Inactivation of the viruses occurs rapidly above 20°C. When temperatures reach close to 40°C, the coronaviruses last only a few hours at most. 3, 4 Epidemiological data on environmental factors in the 2003 Severe Acute Respiratory Syndrome (SARS) epidemic 5-7 showed a significant increase of up to 18-fold in case numbers on cooler days, suggesting that coronaviruses transmit more efficiently during colder weather. 6 . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted May 18, 2020. Although a number of studies have assessed the relationship between temperature and COVID-19 outbreaks, most were conducted early into the outbreak with low case numbers 8 , are pre-prints and not peer reviewed. We therefore sought to collate worldwide data to analyse the correlation of ambient temperature with COVID-19 cases and deaths. In order to analyse this relationship in detail, we also benchmarked the temperatures that the world population experiences.

We considered all cases and deaths related to COVID-19 from the 23 rd of January 2020 to the 11 th April 2020. Data for case numbers and deaths in each country/region were obtained from the COVID-19 Data Repository at Johns Hopkins Center for Systems Science and Engineering. The total number of cases during this period was 1,605,788, which represents the total population of cases and total number of deaths was 103,471, which represents the total world population of deaths.

Historical temperature data were obtained from the Dark Sky weather database (powered by Dark Sky, https://darksky.net/poweredby/). In order to work out average daily temperature, we recorded hourly temperatures for each day in each country/region and computed the mean. This will be referred to as the average temperature. The United States of America (USA), China, Canada and Australia were subdivided into regions as per the International organization for standardization (ISO) 3166-2 standard and recorded temperatures at each of their respective regional capitals. This was done to facilitate the alignment of temperature data with data available from these countries on confirmed cases and deaths in each of their . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 18, 2020. . https://doi.org/10.1101/2020.05.15.20102798 doi: medRxiv preprint 6 respective subdivisions. With India, there were no individual case numbers and deaths available by region. As it is a country that is comprised of many highly populated cities with diverse weather conditions, we separately subdivided India (according to the ISO 3166-2 standard) when determining the temperature distribution of the world population. For all other countries, we recorded the temperature of its capital city.

Temperatures 5 days before cases (17 th January 2020 to 6 th April 2020) were taken to account for the time lag resulting from the median incubation period of SARS-CoV-2. 9 Temperatures 23 days prior to deaths (31 th December 2019 to 19 th March 2020) were obtained to account for the mean duration from symptoms to death of 18 days 10 plus 5 days for the incubation period of the virus. 9 The results were collated using Python Software® and graphing done To compare the world population temperature data, we used the world population of 7.163 billion divided into countries/regions. 11 The average daily temperatures in those countries from 17 th January 2020 to 6 th April 2020 for cases and 31 th December 2019 to 19 th March 2020 for deaths were obtained. We then scaled these data so that it totalled the same as the world number of cases and deaths respectively. This allowed us to plot these data alongside the cases and deaths graphs for comparison. A notional p-value was calculated by the Wilcoxon test, as the distribution of the world population and cases are both non-parametric distributions.

Cases . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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The copyright holder for this preprint this version posted May 18, 2020. periods. [15] [16] [17] [18] The reasons for this enhanced viral spread during colder weather may be due to enhanced shedding of the virus during colder weather 17, 19 , stability of the virus suspended in air droplets 20 or increased viability on nasal mucus membranes cooled by surrounding air. 21 Additionally, cold weather can impair the immune system by inhibiting nasal mucociliary clearance and phagocytosis, diminishing the protective properties of mucus in upper airways 22 , or predispose to vitamin D deficiency due to lower exposure to ultraviolet radiation making people more susceptible to the infection. 23 Based on our analysis, countries should incorporate ambient temperature forecasts into account when developing risk prediction models and even calculating R-nought (number of people one infected person subsequently infects). With no country yet reporting more than 1% of the population infected, the potential beneficial public health effects of "herd immunity" (at-risk people protected from infection because they are surrounded by immune individuals) is still out of reach and it is likely that it will be months to years before a vaccine becomes available for widespread use. 24 Therefore, strict application of public health strategies such as lockdowns, social distancing, testing and contact tracing should be strongly considered for countries heading into temperatures that range between 4°C and 18°C. These . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 18, 2020. measures should also be continued in countries currently experiencing temperatures in this range to assist the prevention of emergence/re-emergence of the epidemic. This is important, as a vast proportion of people infected with SARS-CoV-2 can remain asymptomatic and freely mix with the general population, transmitting the virus. [25] [26] [27] Extrapolating the 2019 temperature data (as shown in Figure 3 ) for the remaining 2020 year, it is possible to predict when regions may approach this dangerous temperature range for enhanced viral transmission. For example, Victoria, Australia will enter this band in mid-May and remain in it until mid-October. Later in the year, with the onset of the Northern hemisphere winter, New York, Italy and Hubei will be in the band again from late October onwards. The identification of these at-risk time periods will aid governments and public health authorities in planning their surveillance and monitoring activities to counter the risk of recurrence of SARS-CoV-2 outbreaks

The key strength of our study is that we included the entire worldwide population of cases and deaths over a 3 month time period. This avoids sampling errors and makes the demonstrated association between temperature and COVID-19 outbreaks significant.

Some COVID-19 cases may have travelled during the incubation period and were subsequently detected, recorded and attributed to another region with a different temperature.

These people movements were not taken into account and may potentially add unintended bias to our findings. We have taken the temperature of each region at its respective capital, but there is likely to be some temperature variance among various locations around the capital region. This may serve to obscure correlations between temperature and COVID-19 cases and deaths. We chose to use the average daily temperatures for our analysis, but . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 18, 2020. . https://doi.org/10.1101/2020.05.15.20102798 doi: medRxiv preprint 1 1 acknowledge that this may not represent the exact outdoor temperatures on particular days when people became infected. Studies showed that the median incubation period of SARS-CoV-2 is 5 days 9 and the mean time to death from symptom onset was 18 days 10 and we used these numbers in our analysis. However, the incubation period can vary from 2-14 days with 1% of cases occurring after 14 days and time to death can vary according to the clinical course of the disease. 9 This may introduce some imprecision in to the histogram that we presented, but as temperatures are unlikely to change significantly over the course of a few days, the overall impact of these variations is likely to be minimal. Some regions may have under-reported cases due to, for example, lack of available testing or being unaware of their asymptomatic carriers. This will likely underestimate the peak infection incidence as regions with the largest outbreaks will have the highest demand for tests or simply assume people are infected without confirmation testing. Our analysis also does not take into account public health measures such as mandatory lockdowns, social distancing and contact tracing measures that could minimize outbreaks. 28 Other environmental factors such as humidity, windspeed and ultraviolet radiation levels as well as regional factors such as population density and social behaviour may also affect the transmission of coronaviruses and its relationship with ambient temperature. 5 Whilst we are aware that some warmer countries such as Singapore have had clusters of outbreaks 29 , this may relate to foreign imports, spread in air-conditioned buildings maintained at lower temperatures or transmitted from person to person via a fomite harbouring in cooler temperatures such as in refrigerators. 30 Conclusion . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 18, 2020. Our analysis shows a definitive association between rates of infection and death from COVID-19 and ambient temperature, with the highest risk being around 9°C. We suggest that countries take ambient temperature trends into account when planning policy on containment strategies such as social distancing and lockdowns to minimize future outbreaks of COVID- 19 . Further studies to assess potential relationships between COVID-19 infection and other environmental factors such as humidity, wind speed and ultraviolet radiation levels may better prepare us to tackle our invisible enemy.

No funding was received for the preparation of this manuscript.

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The copyright holder for this preprint this version posted May 18, 2020. Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.

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The copyright holder for this preprint this version posted May 18, 2020. . https://doi.org/10.1101/2020.05.15.20102798 doi: medRxiv preprint 1 8 Figure 5 -These graphs show changing temperatures on the y-axis (red line) for Hubei (China), Italy, New York, Singapore, Nigeria and Victoria (Australia) from 22 nd of January 2020 to 11 th April 2020 (x-axis). Also shown are the 40%, 60% and 80% CI for the median worldwide temperature for COVID-19 outbreaks (9.12°C). Superimposed on each graph is the total confirmed cases of COVID-19 (black line) at each location, quantitated on the y-axis on the right. These demonstrate the correlation between the regions with temperature ranges in the "red zone" and total number of cases.

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