How the Coronavirus traveled to India

Arjun Ghosh
8 min readMay 16, 2020

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The first cases

The first recorded cases of the coronavirus infection in India were in the southern state of Kerala in late January and early February 2020 of students who returned home from the Wuhan University. The cases were dealt with promptly and by mid-February all three patients had recovered. There were no reported cases of the virus spreading to any other Indian from these three patients. It was at the beginning of March, when the disease had begun to subside in China, that India recorded its second set of Corona positive cases, significantly a set of Italian tourists who tested positive in Delhi after having toured Rajasthan. This was the time when the disease had started recording its steep rise in Italy.

As the virus spread across Europe and beyond, on 11 March the WHO declared COVID-19 to be a pandemic. While on 8 March the Indian government had suspended all visas granted to nationals of Italy, Iran, South Korea and Japan. By 12 March it canceled all visas thus preventing further entry of foreigners to the country. However, the inflow of the virus continued as Indian nationals — tourists and migrants — continued to return home. Special flights were arranged to evacuate Indian nationals stranded at various foreign locations. There was an attempt to check disembarking passengers through thermal checks. “High risk passengers” who were identified were marked to designated quarantine facilities and the rest were advised “home quarantine”.

Lockdown announced

However, there were several reports in the media of people who flouted the “home quarantine” advise and later tested positive for the Coronavirus. As a proactive measure various the Central and State governments took recourse to different social distancing methods since mid-March and partial to total lockdown of the country from 22 March. A total lockdown was announced for the country for three weeks from 25 March. Further, all international passenger flight operations were halted from 22 March, a ban which was extended to all domestic airlines on 24 March. The railways also stopped operating reducing the possibility of vehicular movement of population within the country.

The virus spread and by 14 March India had registered its first 100 Coronavirus cases. At the time of writing the number of confirmed COVID-19 cases in India have crossed 7000. Since, the primary source of the infection is through import, this study attempts to ascertain the routes through which the virus traveled to different parts of India. The data for this study is sourced from the crowdsourced database maintained at covid19india.org. This database is maintained by a team of volunteers who crawl various sources — including government websites, twitter feeds and news portals — to create a multipoint database on each patient. Though crowdsourced this is the most comprehensive open database on the Coronavirus outbreak in India. It maintains details of age, gender, the location of the detection of the infection at the state, district and city levels, contact tracing information and travel information where available. This study has made use of the unstructured travel information recorded in this database to map the migration first as a Sankey Diagram (Figure 1) and then as a GIS mapping. Out of 5352 reported cases till 7 April, travel history was recorded for 1043 patients. The analysis was conducted on the basis of these 1043 recorded cases.

Figure 1: Sankey Diagram of all confirmed Covid-19 cases from India maked with a travel history (till 7 April 2020) [Source of data: covid19india.org]

The Covid19Tracker being a volunteer enterprise has limited resources. It does not have the authenticity of official sources of data. But what has perhaps characterized the Covid pandemic is the lack of accessible public authenticated datasets that makes community and expert intervention possible, both in terms of volunteer effort as well as offering critique that is an important sign of democracy.

The Middle Eastern connection

One of the dominant themes in the coverage of news related to the Coronavirus in the Indian has been an effort to follow the news emanating out the fight against the epidemic in Italy and other parts of Europe and in the United States. From the coverage it would seem that the import of the coronavirus to India and strategies of combating it were to be drawn out of the European, American and in certain cases the Chinese experience. The data, however, indicates that the single largest import of the infection occurred into India from the Middle East — accounting for 396 of the 1043 cases. Europe and North America accounting for 56 and 12 cases respectively. A bulk of the travelers from the Middle East who ultimately tested positive for Covid-19 emerged from Dubai and other locations in the United Arab Emirates (UAE). What is surprising is that the cases of Covid-19 in the UAE have been relatively modest — recording about 2400 cases by 7 April.

Much of the cases of infection emerging out of the Middle Eastern countries were discovered in Kerala — 175 out of 396 — with the rest of the imports being shared by Maharashtra, Haryana, Karnataka and other states. This is significant because for most of March 2020 Kerala recorded the highest number of confirmed cases with the district of Kasaragod being one of the hot spots for the Coronavirus in the country.

Though more than half of the import from Europe came from the United Kingdom, these were distributed among various states. Similar is the case of incidences of the virus coming in from the United States. The other significant band in the Sankey diagram belongs to the movement of Covid positive patients from Iran to the state of Rajasthan. Among them were people who were evacuated from the Covid-19 hot spot country by the Indian government and placed in quarantine camps near Jodhpur in Rajasthan. Among the linkages in transmission within India we find a significant spread of the virus from Delhi to Tamil Nadu.

Now, if we turn our attention to a stacked graph marking the share of the top incidences of confirmed Covid-19 cases in India we find that Kerala which reported the maximum number of cases till 27 March, gradually arrested the growth of the infection till the second week of April (Figures 2 and 3). Which, among other factors, means that the spread of bulk of the infections imported from the Middle East into Kerala was contained.

Figure 2: Share of Top 5 Covid Affected States in India (Till 7 March 2020) [Source of data: covid19india.org]
Figure 3: Share of To 10 Covid-19 affected states in India (Till 10 April 2020) [Source of data: covid19india.org]

The study then maps the entry of Covid-19 to India and within India across time.1 We need to note that since the source dataset does not record the date of disembarking in India by the patients concerned, we have mapped them against the “Date of Announcement” of the result of the Covid-19 diagnostic test. Given that the onset of the symptoms of Covid-19 may take between 2–14 days from the day the patient contracts the virus we can assume that the patients marked on the map would have traveled between 2–10 days prior to the “Date of Announcement’ of result of the Covid-19 test. This shows that for cases that were reported for patients with a history of international travel between 1–19 March an overwhelming majority of them having emerged from the Middle East (Figure 4).

Figure 4: Cases marked as “imported” between 1–19 March 2020. [Source of data: covid19india.org]
Figure 5: Cases marked as “imported” between 18 March and 2 April 2020. [Source of data: covid19india.org]

The picture witness a marked change between 19 March to 2 April (Figure 5) with a concentrated set of cases where the numbers from the Middle East were complemented with a large number of Covid-19 tests that were found positive among those who returned from Europe. Towards the end of this period we find that though there are positive cases reported from those who returned from the US, their numbers are fairly small. Beyond 2 April there are very few cases reported from among people with an international travel history.

Figure 6: Cases marked as “local” with travel history within India between 23 March and 7 April 2020. [Source of data: covid19india.org]

The Indian route

If we turn to the cases in the dataset which are marked as “local” (Figure 6), that is though the patients did not themselves have an international travel history they may have come in contact with certain persons who did have an international travel history, and they did travel within the country. Almost all these cases received confirmation after 22 March. Given that the country was in various states of lockdown since 22 March these cases of travel may have occurred in the fortnight immediately preceding the lockdown or just at its onset. It has earlier been noted that since 12 March various educational and other institutions suspended regular activities and instructed resident students to return to their respective hometowns. At the immediate onset of the lockdown an enormous exodus of migrant labour was reported in the media. The labourers and daily wage earners who were apprehensive of a situation of job loss and hunger due to the lockdown in many cases walked hundreds of kilometers to the apparent safety of their villages.

The visualization of such “local” transmission shows that Delhi was an important source for the spread of the coronavirus throughout the country — particularly Tamil Nadu.

Given that the coronavirus may be constantly mutating an understanding of the sources of its “import” may be useful for studies that examine the behaviour of the virus. Such understanding can hold important pointers to the policy decisions regarding travel bans and monitoring of disembarked passengers during future viral outbreaks. However, the availability of granular open data sources are important for conducting such independent studies. The current study has been conducted on a crowdsourced consolidation of publicly available data. At a time when there is a dearth of publicly available, authentic data sources, it is crowdsourced data interfaces that help us discover stories behind the headlines. Further results may emerge if the study is conducted using more authenticated sources of data.

1The GIS visualizations included in this article have taken assistance from the Palladio an online data visualization tool developed by Humanities + Design Research Laboratory at Stanford University.

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