UV light influences covid-19 activity in the world : trade offs between northern subtropical, tropical, and southern subtropical countries

12 min readApr 2, 2020

Although UV light has the ability to inactivate viruses, it may be meaningless in areas with high air pollution where UV light turns into heat.

UV (ultraviolet) light is an important factor should be considered to predict coronavirus epidemic growth pace. UV is different from weather temperature since UV is electromagnetic wavelength from 10 nm to 400 nm in size, shorter than of visible lights. For some people, UV light can lead to cancer from unprotected sun exposure, however, for tropical people, which have been used to live in such condition, have resisted from negative effect high UV index. Moreover, UV has the capability to inactivate virus. This conclusion has been discussed deeply with biological experts (Sutiman et al.).

published in preprint: https://www.medrxiv.org/content/10.1101/2020.04.30.20086983v1.full.pdf

Firstly, let us introduce you to some references:

Covid-19 can actively live airborne and in surface (see : https://www.weforum.org/agenda/2020/03/this-is-how-long-coronavirus-lives-on-surfaces)

Pandemics can cause severe mobility and mortality over wide geographic area (see : https://www.ncbi.nlm.nih.gov/books/NBK525302/).

The coronavirus spreads are related to carbon emission (see : https://www.nature.com/articles/d41586-020-00758-2). Note that smoke particulate is able to weaken the UV light ability to be active in the air.

The frequent asked question (FAQ) about UV and ozone can be found in this site (see : http://www.bom.gov.au/uv/faq.shtml)

The vaccine development is not effective and taking a long time to be found (see : https://www.cnn.com/2020/03/31/us/coronavirus-vaccine-timetable-concerns-experts-invs/.) Natural immune is somewhat more desirable.

Example of references about virus inactivation due to ultraviolet (see:

)

Some technologies been developed by making use of UV light (see:

UV Index in Indonesia is very high (see : https://lifestyle.kompas.com/read/2010/06/25/05061127/indeks.radiasi.ultraviolet.indonesia.sangat.tinggi)

UV index over the world taken from woeurope.eu

The above figure is uv index over the Asia and Europe that seems to be correlated to covid pandemic rate over countries. Most of high rate of covid-exposed countries are located in subtropical area, conversely, low rate of covid-exposed countries are spreading throughout tropical areas. Concurrently, tropical countries have high index of UV over time and subtropical countries are interchanging between low and high index of UV depending on the season.

Confirmed cases over the world taken from John Hopkins University & Medicine on April 4, 2020

The confirmed cases map above seems to be correlated to UV index map where the majority of confirmed people live in the northern subtropical countries.

Now let's do some research ...

Data are gathered from January 22, 2020 to March 28, 2020

How coronavirus spreads differently in each country.

Figure 1. The pandemic growth of countries which have low level of growth rate. It is shown that confirmed accumulation in range of 0–2000+ people

Coronavirus which causes the illness known as covid-19 was first reported in China at December 2019. In March 2020, this disease was spreading to at least 178 countries and territories. In some countries, the accumulation of confirmed cases varies from 0 to more than 120000 people over time (figure 1 and 2). This data shows that this virus has the ability to spread easily and quickly. Indonesia as one of the countries affected by coronavirus shows the number of sufferers reaches 1000 people (figure 1). The number seems to be high but it is still lower when compared to other countries such as America, Italy, France, Netherlands, and Iran (figure 2).

Figure 2. The pandemic growth of countries which have low level of growth rate. It is shown that confirmed accumulation in range of 0–120000+ people

Figure 1 and 2 show the spread of coronavirus in some countries that less than 5000 confirmed cases and more than 5000 confirmed cases, respectively. The accumulation of confirmed case grows exponentially with different rate in each country. Indonesia grows in very little rate compared to US, Italy, France, Netherlands, and Iran.

We can easily cluster those countries by its location using pandemic growth information. For example, referring to above figures, Malaysia, Indonesia, Thailand, and India can be grouped into one cluster while US, Italy, France, Netherlands, Iran, Japan, and Russia in another cluster by its tropical and subtropical continent, respectively. Japan, however, has higher UV index compared to US, Italy, and Russia and its UV index grows over time as spring season is coming. We will show the figure later. Russia that has low population density seems to have anomaly here and of course another parameter such as humidity, air pollution or even economic relation with epicentrum country can be taken into account in future studies.

Per day confirmed cases

Before, let us show the covid epidemic growth in several countries and how exponential its slope.

Figure 3. Daily confirmed case in low growth rate countries

The development of confirmed cases of people infected with the corona virus tends to increase every day (figure 3 and 4). This trend shows how quickly this virus spreads in humans. Inside human body, this virus takes time to show symptoms of illness, it makes this virus easily to spread among people before the carrier notice about it.

Figure 4. Confirmed case per day in some countries

Highest confirmed case reported in US reaches around 20000 people in a day (figure 4).

Daily cases vs UV index

Now we look into the pattern of daily confirmed cases and UV index in several countries.

As a remainder, UV index can be measured as below (https://www.who.int/uv/publications/en/UVIGuide.pdf):

0 to 2: Low Risk of harm from unprotected sun exposure

3 to 5: Moderate Risk of harm from unprotected sun exposure

6 to 7: High Risk of harm from unprotected sun exposure

8 to 10: Very High Risk of harm from unprotected sun exposure

11+: Extreme Risk of harm from unprotected sun exposure

The calculation of UV index can be found in this site https://www.epa.gov/sunsafety/calculating-uv-index-0

It possibly harms to people that are not used to live in such an extreme UV index, however, it can reduce virus activity. The people who live in high UV index areas such as Africa and other tropical countries have already long-adapted in such situation. They may take advantage that pandemics are not as exessive as subtropical countries.

Figure 5, UV Index over time in many countries

Based on the figure 5 above, northern subtropical countries have UV index grows over time as the cold season ended and spring season is coming. Australia as a representation of subtropical countries has its UV index decreasing over time as summer season ended and fall season is coming. In Atlanta, area which is located in central area of US, has higher UV index than of in New York, even though they both grow concurrently over time. Interestingly, New York area has lowest UV index compared to others of which has UV index of 1 to 4 over time.

China case : recovering with the help of UV light and lockdown?

Figure 6. Accumulation of confirmed case in China until the days of growth halt

Figure 6 shows graphs of confirmed case accumulation over time in China. There is an interesting fact that Hubei province in which Wuhan city is located does not extremely spread covid-19 to other provinces.

Figure 7 shows graph of daily confirmed cases in China. There is also an interesting fact that Hubei province in which Wuhan city is located does not extremely spread covid to other provinces. The daily confirmed cases show that other provinces do not show significant confirmed cases compared to Hubei province. This is related to China government effort to carry out tight lockdown in the epicentrum (Hubei area) thorough screening, testing and contact tracing programs, as well as bringing in early social distancing whilst also light lockdown in another area (see : https://www.theguardian.com/world/2020/mar/19/chinas-coronavirus-lockdown-strategy-brutal-but-effective)

The reason can be two-fold: the help of lockdown with its social distancing and by the help of increasing UV index as shown in figure 8 below

Figure 8. The UV index over time in China. The four stations are presented which are Tianjin and Dalian in northern China, Mount Waliguan in central China, and Baoding represents middle and southern China.

Figure 8 shows that UV index in China is monotonically increasing over time during pandemic period. The nearest GAW station to Hubei province is Baoding station in Hebei province. At that time, the lockdown gave Hubei’s air the spaces for UV to take over as the air pollution was gradually reduced.

Tropical vs Subtropical : interesting characteristics

Figure 9. The covid-19 pandemic growth in north sub tropical countries (blue), tropical countries (green), and sub tropical countries (red). Note that US, UK, Italy, or Spain is not included due to very high growth rate.

Figure 9 above shows pandemic growth in tropical (green), northern subtropical (blue), and southern subtropical (red). It is quite interesting that the blue countries grow exponentially over time since the initially confirmed people are recorded, with sharper, and faster than the green and red countries. The green countries grow sharper and faster than red countries, even though some countries have crosspoints with each other. The overtaking points indicate that there exist growth pace that is becoming slower than the other, and vice versa. This happens between two adjacent groups either blue with green or green with red. This phenomenon possibly can be explained in Figure 10 below.

Figure 10. The UV index alteration over time in north sub tropical countries (blue), tropical countries (green), and sub tropical countries (red).

Figure 10 above shows the change of UV index over time in northern subtropical countries (blue), tropical countries (green), and southern tropical countries (red). We can easily understand that the blue and green countries are monotonically increasing over time while the red countries are monotonically decreasing. This phenomenon regards the changing season between cold to summer in northern countries and, conversely from summer to cold season in southern tropical countries. The green countries rarely have UV Index below 6. UV Index behavior of blue, green, and red countries are concurrent with the accumulation of confirmed covid-19 over time in Figure 9. Some blue countries are starting to be sloper as higher UV Index and with proper social distancing.

The anomaly: Canada, Russia, and Japan

While it is evident that northern subtropical countries suffer high rate of pandemic growth, some countries like Canada, Russia, and Japan do not suffer a similar pace compared to the majority of northern subtropical countries. Even though their pace is still a comparable or little bit higher than tropical countries, we should investigate other factors. The candidate factors are the intensity of economic activity especially with the source of pandemic country, the density of residents, social behaviour, air pollution, and humidity. For example, the Japanese people have a tradition of social distancing by not doing intense social engagements, especially with foreign or stranger people and have minimum air pollution that we still can see stars in the sky at night.

The southern subtropical countries: Should they anticipate?

Even though we still do not know the final growth curve, by the aforementioned evidence, they should be prepared the worst case. The dynamic patterns of the current situation show that some southern subtropical countries are starting to grow exponentially as shown in Figure 9. Especially, for airborne covid-19 viruses that exist in the air, spreading vastly in the air. They can perform early lockdown before exponential increase whilst also arrange UV treatments.

Growth Slope : see the change over time

Figure 11. Example of local slopes and global slope

We use local and global slopes as parameters to see how related the UV index with the accumulation of confirmed covid-19 growth as shown in Figure 11. Tangent line is used as the slopeness metric of the graph. The difference between local and global slope is that local slope uses each local point in time frame to estimate the tangent line while the global slope is measured from the last point. The global slope gives more global growth performance.

Correlation Test : to see the relationship between parameters

Let me remind you that:

1.0 = positively correlated ; for instance, if A increases, B also increases, and vice versa
0.0 = no correlation ; for instance, if A increases, B does not change, and vice versa
-1.0 = negatively correlated ; for instance, if A increases, B also decreases, and vice versa

Let us introduce you to several parameters to be tested:

UVIEF: cloud-free,erythemal (sunburn),UV index
UVDEF: cloud-free,erythemal (sunburn),UV dose,[kJ/m2]
UVDDF: cloud-free,dna-damage,UV dose,[kJ/m2]
UVDEC: cloud-modified,erythemal (sunburn),UV dose,[kJ/m2]
ozone: local,solar,noon,ozone,column,[DU]

UV index is a measure for the effective UV irradiance (1 unit equals 25 mW/m2) reaching the Earth’s surface in clear sky. http://www.temis.nl/uvradiation/UVindex.html

UV dose is the effective UV irradiance (given in kJ/m2) reaching the Earth’s surface integrated over the day and taking the attenuation of the UV radiation due to clouds into account. http://www.temis.nl/uvradiation/UVdose.html

Total column ozone is the total amount of ozone in a column extending vertically from the earth’s surface to the top of the atmosphere. It is measured using ground-based stations and satellites and is reported in Dobson units (DU). The ozone hole is defined in terms of reduced total column ozone — less than 220 DU. https://www.geographyandyou.com/total-column-ozone-in-the-atmosphere/

Correlation test of the world data : Data preparation

Countries to be included :

Australia, Thailand, India, Japan, US, Italy

Global Atmosphere Watch (GAW) station to be used :

AcadiaNatForest_USA
Gibilmanna_Italy
Chiang_Mai_Thailand
Hyderabad_India
Adelaide_Australia
Naha_Japan

Correlation test results map of the world:

Figure. 12. Correlation map between parameters of the world

average of UV index and average of ozone over time are correlated to global slope of confirmed cases accumulation by -0.86 and 0.94, respectively

Meaning that the higher UV Index is, the lower the growth rate of covid-19 pandemic would be, and vice versa with a correlation of -0.86. Conversely, the higher the ozone value is the higher growth rate of covid-19 pandemic would be, and vice versa with a correlation of 0.94 as shown in Figure 12.

the global slope of UV index alteration over time is correlated to the global slope of confirmed cases accumulation by 0.7

This is understandable since the UV index in northern subtropical countries tends to increase over time indicated by high tangent value, however, the growth rate of covid-19 pandemic is still increasing even though the pace is slowing down. Conversely, in southern subtropical countries, the UV index tends to decrease over time making the tangent value to be low even minus. We should wait for the next several months to see whether southern subtropical countries will exponentially increase the confirmed cases or not as data taken only until March 28, 2020.

Correlation test of China data: Data preparation

Provinces to be included :

Tianjin, Hebei, Liaoning, Qinghai

Global Atmosphere Watch (GAW) station to be used :

Tianjin_China
Baoding_China
MountWaliguan_China
Dalian_China

Correlation test results map of China:

Figure. 13. Correlation map between parameters of China

Average of UV index and average of Ozone over time are correlated to global slope of confirmed cases accumulation by -0.86 and 0.94, respectively

Meaning that the higher UV Index is, the lower growth rate of covid-19 pandemic would be, and vice versa with a correlation of -0.86. Conversely, the higher the ozone value is the higher growth rate of covid-19 pandemic would be, and vice versa with a correlation of 0.94 as shown in Figure 13.

Conclusion

While UV index and Ozone are correlated with global spread of corona pandemic, we believe it is not just a standalone factor. There are some other factors such as economic activity and population density influencing the spread and growth of coronavirus cases. However, UV light and ozone are strong enough to be taken into account to minimize the global covid-19 pandemic effect. In the cities where there is heavy air pollution, the high UV index might be no meaning in terms of inactivating the virus. Next, we would like to investigate on a smaller scale in one nation such as Indonesia. Another thing is we are preparing to predict when pandemics will end in each country using Deep Learning model.

Suggestion

Based on these findings, we would like to give suggestions that:

Gradual lockdown from loose to tight in southern subtropical countries in accordance with UV index over time. It might be taken into account to reduce the economic burden.
Tropical countries might take advantage of its high UV Index in the entire session but has to keep anticipating.
Special attention in the central economy area where there is heavy air pollution should be considered because the high UV index does not have enough potential to inactivate the virus. Meaning that it should be anticipated that the exponential phase will be high.

Data source

Time series data are gathered from https://github.com/datasets/covid-19/tree/master/data for corona cases data and http://www.temis.nl/uvradiation/UVarchive/stations_uv.html for UV index and Ozone data

UV light influences covid-19 activity in the world : trade offs between northern subtropical, tropical, and southern subtropical countries

Written by novanto yudistira