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:
- 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.
- 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.
- 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.
- 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