Temperature threshold: High temperature
Interestingly, countries having temperature more than 300°K (27°C) showed unusually low death rate compared to the overall statistics. Countries from the South Asian Association for Regional Cooperation (SAARC), South East Asian Countries (SEAC), the African continent and Australia all lied in that zone and all have low death counts (Fig. 1, Fig. 2a). African countries lying in that temperature zone reported insignificant infected cases as well as deaths. That temperature zone excluded countries with higher reported case among African continent (countries of northern boundaries e.g., Algeria, Egypt and Morocco and Southern boundaries e.g., South Africa). For Australia, that statistics of the reported cases (and deaths) were 5224 (23); in fact, no death was reported till 3rd of April1 in regions when the temperature is higher than 300°K (27°C). Almost all reported cases and deaths for Australia were around South West part of the country where the temperature was below 300°K (27°C) (Fig. 1 and Fig. 2a). Few other countries falling in that temperature threshold with reported cases (and deaths) were Malaysia 3116 (50), Singapore 1049(5) and Thailand 1875 (15).
Certain clinical tests found the infection rate for some seasonal air borne virus was reduced to zero at temperature 30 °C at certain humidity level11. Here we show that the vulnerability to COVID-19 is reduced drastically even at 27°C, without considering any effect of humidity. In addition to that, when the temperature was above 305° K (32° C), an unusually low number of the reported cases, as well as deaths, was observed1.
These analyses indicated some rough temperature threshold for the spread and vulnerability to COVID-19 as follows: i) 275° K (2° C) to 290° K (17° C) - maximum reported case as well as death; ii) <275° K (2° C)- death reporting was low; iii) 300° K (27° C) and above- significantly less number of reported death compared to overall population; iii) >305° K (32° C)- an unusually low number of reported cases as well as deaths.
Fig. 2b is the spatial plot of global temperature for April which is tested again and the main conclusion relating to temperature threshold and vulnerability remain the same. Climatology of temperature is prepared globally for different months (Fig. 3-8). Following the current analyses, it would indicate predictive maps of vulnerability for different months based only on temperature. We find Fig 2b is consistent with Fig 3 (bottom) and Fig. 2c with Fig 3 (top), which are for the month of February and March respectively. As we verified the last February and March 2020 with the climatology of those two months, we may expect the predictive maps would be very similar for other months too. Thus, climatology map of temperature can give ideas of vulnerability level to different countries month-wise and the direction of transitions. It will be important for every country for future preparedness.
The vulnerability to the disease worldwide was analysed based on certain data on the day of 1st May. To examine that data till the 1st of May (Table 1) we compared global temperature map from 15th Feb till the end of April (Fig. 2c). We find the result is again consistent.
Examining Reported Cases and Deaths
Based on location, testing and other various reasons reported cases are likely to vary. Until a high number of populations is tested the case reporting may be sometimes meaningless. As death reporting is usually authentic, we considered ‘deaths’ as a better metric. Moreover, the absolute number of deaths vary based on population. Hence to analyse the degree of vulnerability, death/Million population of a country is chosen as the best indicator in this analyse.
In Table 1, we have presented a few statistics showing situation update/ performances of various chosen countries 26. Some countries, especially those are developing could have poor reporting strategy and inadequate facilities. Tests /Million population are expected to be comparatively low for those countries, as also reflected in Table 1 (last column). We should note that data or statistics presented in Table 1 could vary slightly and may not be accurate. However, those limitations do not affect the main results of our analyses.
Test /Million populations were maximum for Iceland, which was reflected in the highest number of infected cases per million (column 4). Death/Infected (column 5) is a parameter that could indicate the performance of medical treatment country-wise and expected to be lower for developed countries. However, it is also linked with the number of more overaged population and number of testing etc. Death/Infected (%) was highest in European countries in spite of advanced health care system, that may indicate a high ageing population. The same was the lowest for Singapore (.1%), which had high testing rates amongst all warm countries.
Data of all countries from South Asian Association for Regional Cooperation (SAARC) were presented which are Afghanistan, Bangladesh,  Bhutan, India,  Maldives, Nepal, Pakistan  and Sri Lanka. All countries of South East Asian region were also presented in Table 1. Those are Singapore, Cambodia, Malaysia, Vietnam, Thailand, Indonesia, Philippines and Myanmar. Among those, some are very popular tourist spots and some are popular international business hubs where more transmission of the disease by foreign travellers are expected. In spite of the varied level of testing, infrastructural facility, population density, varying degree of lockdown restriction and many dissimilarities among each country there was still one common factor. All those countries had very less death per million population. For SAARC countries it was 2 and under; whereas, for South East Asian countries (SEAC) it was 6 and under. Among these countries, Singapore did maximum testing per million, which was even comparable with developed countries. That large count was reflected in the higher count for infected per million compared to other countries in that group, though not in the death count. Among that group of countries, the number of deaths in one day (01/05/2020) was higher in India and Pakistan compared to the rest (column 6), which was a common reflection of their high population.
Following Table 1, we found the least vulnerable countries had a very less count of death per Million, which was under 1. That count for less vulnerable countries were 10 and under. Result of few Moderate cold countries and very cold countries were also presented. For moderate cold countries, the deaths per million was very high which even exceed 400 in some countries. Though the USA ranked first in terms of total number of deaths and reported cases1, but being 3rd largest populated countries in the world27, the ranking of the USA in Table, 1, column 3 was lower than in European countries. For very cold countries that count was less than 100 for most cases.
Following temperature thresholds, we categorised countries based on vulnerability as follows:
Category I: Moderate Cold - between 275°K (2°C) to 290°K (17°C) - Most Vulnerable.
Category II: Very Cold – less than 275° K (2° C) - Moderate Vulnerable
Category III: Moderate warm – greater than 300° K (27° C) - Less Vulnerable.
Category IV: Very warm – greater than 305° K (32° C)- Least Vulnerable.
There could still be a very few countries suggesting as outliers. Those could be related to relaxed/ effective social isolation policy and preventive measures, low/high testing facility, relaxed/ regulated overseas arrivals, poor/advanced infrastructure, inadequate/ appropriate medical intervention on time, other favourable/ unfavourable atmospheric conditions etc.
Statistical Analyses
Fig.9 showed vulnerability to COVID-19 measured in terms of Deaths per Million, upto 1st of May, 2020. Fig.9a suggested all Warm countries together (SAARC and South East Asian countries (SEAC), continents of Australia and Africa) had significantly low death rates compared to cold countries. Mean and standard deviation of moderately cold (395.8, 125.0), very cold (41.5, 34.8) and warm countries (2.1, 2.4) suggested a clear distinction. In the group of warm countries, there were enough dissimilaities among each other in various respect (varied testing level, popular tourist destination, infrastructural facility, other atmospheric conditions, developed/developing status of countries etc.). The low mean and standard deviation clearly indicated how strong was the role played by temperature. The method of mean difference is applied among the three categories and to test the level of statistical significance ‘t’ test is used. The difference between each other in the three categories are significant even at the 99% level. In Fig. 9b, we further elaborated on warm countries and presented box plots focusing on countries from SAARC and SEAC. Each group comprises of a total of 8 countries. The SAARC group of countries indicate the lower mean value (1.0) and standard deviation (0.8) than the group of SEAC (2.6 and 2.2, respectively). Fig. 9c further focused each individual countries from Fig. 9b. Among SAARC countries, Pakistan, Afganisthan and Maldives showed highest rate; while from SEAC, countries with high death counts are Combodia and Philipines. Fig.S1 is same as Fig. 9 though considered reported Cases per million instead of Death. Countries with more number of testing sometimes report more cases (e.g., Singapore, Maldives and Iceland).That is one of the reasons for large standard deviations in Fig S1a. Like Death, there is a very clear distinction between three categories (Fig S1a). In Fig.S1b, we excluded two outlier countries Singapore and Maldevis those did very high testing compared to the rest. The boxplot of SAARC and SEAC do not differ much. In Fig.S1c too, we excluded those two outliers for general comparison. As the reported case is heavily dependent on number of testings and other factors, rankings of individual countries in Fig.S1c differ to that from Fig.9. Among SAARC countries, the ranking of Pakistan was highest for both, the death as well as reported cases per million.
Effect of Temperature Regionally and Transition Phase:
Regional temperatures within a country can vary to a large degree, (even ~ 25° C for the USA, Fig. 2). Hence vulnerability of any country will also depend on regional variations of temperature. In Fig. S2a, we showed that the southern part of Canada was mostly affected compared to the rest of the country. Interestingly, that region only lied in the most vulnerable temperature zone (Fig. 2c). A transition was noticed from March to April and more parts of southern Canada are now entered in moderately cold category in May indicting a rise in vulnerability. The spatial plot of Canada (Fig. S2a) and temporal pattern (Fig. S2b) indicated such features. The daily death count increased during the beginning of April (Fig. S2b). A very high number of daily deaths were reported on the 1st of May (Table 1, 6th column), which was comparable to most vulnerable countries.
In spite of a lockdown situation globally8 if there was an increase in vulnerability to some countries that needs attention too. Since the end of April, many countries started moving from one vulnerability state to others, e.g., Russia, Canada and some Scandinavian countries. For Russia, new cases reported on 7th May is 10,559, which is 2ndhighest reported case after the USA26. Canada also reported very high death on that day, which was 189, and again comparable with vulnerable countries26. For Sweden, the death reported on 7th May was 87 which was relatively high compared to the overall population of 10,089,79526. These countries were very cold in March and at the beginning of April and now phasing out to moderate cold phase.
A recent research19 studied the effect of temperature on the spread of COVID-19 in Italy. It showed only 2° C rise in temperature can have a comparable effect on the transmission of the virus. The effect of small change in temperature even for 2° C to 2.5° C was analysed and discussed for a few continents in Fig S3 (Europe), Fig. S4 (Africa) and Fig. S5 (South America).
A spatial plot particularly focused on Europe (Fig. S3) suggested that UK was still in the most vulnerable zone in April; whereas, southern Europe turned warmer (Fig. S3 a and b). Scandinavian countries like Sweden started entering into most vulnerability zone from moderate vulnerability state (Fig. S3 a and b).
For Africa, the region of least vulnerability was marked (Fig. S4). The temperature increased around latitude 15° N in April and Table 1 (6th column) showed no new death was reported to those countries. Questions could be raised about poor testing and reporting in those African countries. One reason could be as death was reported zero, those underdeveloped countries may not have considered testing a priority. Moreover, in Australian continents without much of an issue of testing and reporting also suggested similarly. In fact, part of western Australia and northern territory (least vulnerable region, Fig. 1) did not have deaths and practically few reported cases 1(hence not shown in Table 1). A shift in high temperature region in Africa from south to north during March to April gave an indication of how the vulnerability can shift regionally and gave rough time estimations of that transition.
As 2° C change of temperature can influence the transmission of the disease19, we wanted to confirm that for South America (Fig. S5). Some countries from South America suddenly started an increase in deaths and reported cases. On 7th May, Brazil reported new daily death 667, the 2nd highest after USA26. The lowering of temperature in Southern Brazil (297° C to 291° C in April) is clearly distinct in Fig. S5b to that from Fig. S5a.
In terms of population, three highly populated countries are considered the USA, Brazil and India (world ranking 3rd , 6th and 2nd respectively)27. A plot of recent daily death was presented for those three countries (Fig. S6). The USA, a vulnerable country showed a very high daily count, Brazil now in a transition phase from warm to cooler state, suggested high death count with a comparatively steeper rise in very recent periods. India the less vulnerable country is now moving from warm to warmer. It reported much less death count compared to the rest two.
Fig. 10 showed daily confirmed COVID-19 deaths per million in a form of rolling 7-day average. Those statistics were consistent with the number of death counts per million (Table 1, 3rd column). There are clear distinctions throughout the time period among moderately cold, very cold and warm countries. All warm continents e.g., Asia, Africa and Australia, those belonged to the less vulnerable category, suggested a very nominal daily death count rate compared to the rest (not visible as merges with X axis). The bottom three curves are for Russia, Brazil and Canada respectively. All three are showing a rising trend and we discussed earlier those three are in the transition state. Russia and Canada are turning from very cold to moderate cold; whereas, Brazil from warm to cold. For the USA, UK, Italy and Spain all suggested very high count throughout and all achieved a peak and now in the declining state. During the declining phase, the temperature was also increasing.
Based on the discussion, it is possible to determine the vulnerability of a specific country as a whole and region-wise during different time periods. Another point is worth mentioning that this is an extremely contagious disease and single contamination through a foreign career/traveller can multiply exponentially among locals. Megapolises like New York, Mumbai, London are expected to be infected more than its suburb and it is, in fact, the case. All those factors were also considered while analysing the statistics.
Possible Solutions:
The above analyses highlighted that temperature plays an important role in transmissions of Coronavirus12,13,14,15,17 that include COVID-19 19,20,21. Warm temperature drastically reduces its impact. Hence following urgent measures (also mentioned earlier 22, 23) are proposed to arrest and stop the outbreak:
  1. Using the Sauna facility: Usually hotels, gyms, leisure centres have existing Sauna facilities which people can start taking advantage of immediately. Mobile and Caravan Sauna facilities can also be thought of by higher authorities.
  2. Using Blow dryers: The virus enters through the nose and sticks and attack the nasal cavity 3,7. Intake of hot air through the nose a few times a day can be useful.
  3. Portable Room Heater: People can be close to a portable heater with comparative high temperature say, twice a day and preferably for half an hour. Being portable in nature, it can be moved around and many people can avail that facility in a flexible way. Room heaters can also be useful for disinfecting purposes.
  4. Disinfect any place using high temperature: Before the start and end of offices, school or business, the air-conditioning temperature of the premise may be kept, say, 40 ºC or above for sometimes (say, half an hour) to disinfect. The optimal level (temperature and time) can be tested very easily. For airports, train and bus, that method of disinfecting could be useful. For any external object or material, disinfecting using high temperature could be a useful solution.
The main point in this analysis is that the virus is very sensitive to temperature. Based on that knowledge these few measures are proposed. Many simple, easy procedures serving the purpose can be thought of; some could be applicable to warm countries and poor, remote, rural communities.
Study showed SARS-CoV-2 is more infectious than some other Coronavirues34. The usual incubation period for COVID-19 is around 14 days7. The virus can stay in the human body for a few days without showing symptoms though they still could be a carrier 3,7. As it is difficult to trace mild or pre-symptomatic infection, it has greater epidemic potential34. These measures described above could be very effective when people are in the asymptomatic or pre-symptomatic state. It is noteworthy that when people already developed major symptoms then this method will not be effective and proper medical advice need to be solicited. Given the emergency situation, lots of treatment/ medicines are desperately tried which are fraught with risks of serious side effects. On the contrary, this solution has practically zero side effects. This study suggests the majority of world populations need to be well prepared before the coming winter. This is an extremely contagious disease3,7. Social isolation and lockdown can be a temporary solution, as the economy and mental health also need attention.
These four measures alongside other similar simple solutions are likely to reduce the spread dramatically. If few of these measures are implemented worldwide, it will have a major impact to arrest the spread of the virus.
Conclusions:
This article investigated the influence of temperature globally in the spread and vulnerability to COVID-19. It indicated that temperature was a crucial factor in transmitting the virus. For the spread of the virus, the most favourable state was moderately cool places; whereas warm countries and places were likely to be less vulnerable. Similar temperature dependency was also noticed in previous clinical trials those involved other Coronavirus (MARS, SARS etc.) and seasonal influenza/ flu virus. Four different categories of vulnerability are identified based on temperature variations - which are moderate cold, very cold, moderately warm and very warm. For analysing vulnerability, death per million population was considered as a useful and effective metric. The maximum reported case, as well as death, was noted when the temperature was between the threshold of around 275°K (2°C) to 290°K (17°C). Based on temperatures of March and April we specified some countries too; the USA, UK, Italy, Spain belonged to this category. The vulnerability was moderate when the temperature was less than 275° K (2° C) and countries in that category for March and April were Russia, parts of Canada and Scandinavian countries. A significantly lesser degree of vulnerability was noted for countries with temperatures 300° K (27° C) and above. SAARC countries, South East Asian countries (SEAC), African continent and Australia belonged to that category during March and April. In fact, when the temperature was more than 305° K (32° C) there was an unusually very low number of reported cases as well as deaths. Some parts of Australia and African continent showed such behaviour in March, April. The vulnerability to the disease is significantly different, between each other, for moderately cold, severe cold and warm countries. For warm countries, further analyses on the group of SAARCs and SEAC were conducted and individual countries were also compared.
We provided maps of temperature to identify countries of different vulnerability state in different months of the year. We discussed that based on temperature variation, countries can move from one vulnerability state to the other. For e.g., parts of Russia, Canada started entering from severe cold to moderate cold state at the end of April; whereas, Brazil and few warm countries from South America moved from warm to less warm state. In spite of lockdown situation worldwide, those countries reported a sudden rise of death and infected cases at the beginning of May.
We discussed daily confirmed COVID-19 deaths per million over the period, in a form of rolling 7-day average. It was consistent with the number of total death counts per million. There were clear distinctions throughout the time period among moderately cold, very cold and warm countries. All warm continents e.g., Asia, Africa and Australia, those belonged to a less vulnerable category, suggested a very nominal daily death count rate compared to the rest. The USA and European countries showed a decline in the recent period, while Russia, Canada and Brazil are showing a rise.
Our analyses can also give some idea for regional variation of vulnerability of various countries and we specifically discussed that for Canada. Spatial variation within continents were discussed for Europe, South America and Africa for the month of March and April. Our analyses could indicate, which countries are in favourable/ worsening state in the coming months based only on temperature variation. As regional temperature played a very important role in the transmission and spread, our result and future predictive maps have a major implication for future planning.
We discussed that, like other similar category viruses, this virus is also very sensitive to temperature. It gave us a valuable insight that regulating temperature level can provide a useful strategy to arrest and stop the outbreak. Based on that knowledge, some urgent solutions are proposed. It is very cost effective and practically without side effects. To adopt these solutions no vast amount of funding is required. Another novelty of such an approach is- it can be applied overnight and implemented immediately across the globe. These measures are likely to reduce the spread of the disease dramatically.
Acknowledgement. This study did not receive any funding and there is no conflict of interest (financial or non-financial). Figures (2-8) and Fig. S3-S5 are generated from the NOAA/ESRL Physical Sciences Division, Boulder Colorado web site at https://psl.noaa.gov/data/ composites/day/. This article was submitted to Plos on 17.05.2020 and lied with them till 19.06.2020 and was not sent for review. It has two earlier preprint version Commentary; i) Roy, I. (2020), Combating recent pandemic of COVID-19 - An urgent Solution. March, 17th2020, DOI:10.13140/RG.2.2.22632 .83208 and ii) Roy, I. (2020), Atmospheric Variables and Additional Urgent Solutions for Combating COVID-19 dt 9th April. https://www.preprints.org/manuscript/202003. 0366/v2