As at 10 am Geneva time on 28 January, 4593 cases had been reported of pneumonia caused by the novel coronavirus now known as 2019-nCOV, of which 106 had been deadly [1] . There are reported outbreaks of 56 cases in 14 countries: Japan, Republic of Korea, Viet Nam, Singapore, Australia, Malaysia, Cambodia, Thailand, Nepal, Sri Lanka, USA, Canada, France and Germany [2, 3] . Coronavirus, temporarily named as 2019-nCoV, belongs to a large family of viruses that can cause many different infections, from a cold to acute respiratory failure syndrome [4] . The one from Wuhan is only the 7th that is known to harm people [5] .
There is no single effective way to fight coronaviruses, but only measures to help relieve their symptoms. The symptoms include fever, respiratory problems and lung infiltration [6] . As at 10 am Beijing time on 22 January, Wuhan international airport was closed due to potential for international dissemination of this disease via commercial air travel [7] . Other public transportation in the city are also closed.
Infodemiology is an area of science research that focuses on scanning Internet, publicly available data and other sources for user-contributed health related content [8] . In last year's many researches has been done using data collected from Google Trends (GT), Google Flu Trends or Google Health API. There is growing number in research using GT [9] . Before GT was released, early studies were done on Google Flu Trends, a source for queries connected to diseases [10] .
GT is the source of reversed engineered data. It shows what was searched in Google and the data is normalized in terms of search frequency and presented in relative search volumes. Data is segmented into years, months, days, and into geographical regions. Researchers are able to compare maximum 5 keywords using segments in one try. Studies on GT can be divided into four areas: infectious diseases; mental health, other diseases and general population behavior [11] and mainly are used to examine the seasonality [12] .
Looking at recent studies, GT was used to track infectious disease data on chickenpox [13] , Lyme [14] , the Ebola epidemic [15] , syphilis [16] , conjunctivitis [17] dengue fever [18] , HIV [19] , sepsis [20] , plague [21] and track influenza epidemics using climate data. GT is also used to forecast [22] , real-time surveillance [23] or to prevent [24] diseases.
The motivation behind this communication is to analyze how search demand for information about coronaviruses is shared worldwide. There is no doubt, that people express own interest by searching information and using search queries.
Data is collected from GT (https://trends.google.com/trends). GT presents normalized data. The highest interest on search query is expressed by 100, whereas lack of interest or not enough data are expressed by 0. GT contains data from different geographical locations, segmented to countries, territories and cities. GT allows to set custom time range. Queries are collected from five specialized search engines: Web, Image, News, Google Shopping and YouTube Search.
In this case data is retrieved, a two days before since the first mention of this disease is noted by Google, as December 31st, 2019. Data come from Web Search for two geographical settings. First setting is worldwide, to see the interest in coronaviruses over the world. The second is only China. Since Google does not operate in China freely, it needs to be examined separately.
The first approach is to collect worldwide data on keywords: coronavirus, SARS and MERS. Figure 1 shows the worldwide interest in search from December 29th, 2019 to January 26th, 2020. GT has gap of two days of current data. The last available data is from January 20th, 2020. Figure 1 shows that information outbreak of interest in coronavirus as well for SARS started on January 20th, 2020. Until January 16th, a relative interest worldwide was expressed in SARS. Up to January 26th, there is no data on 2019-nCoV term. It means that people do not use the specialized name but refer to it by using a general term. It is visible on trend line, that increasing interest is slowing between 25th and 26th of January.
As of January 26th, interest in coronavirus, SARS and MERS was expressed in 44 countries, according to Google Trends web search data. (See Table 1 ). Search term popularity is relative to the total number of Google searches performed at a specific time, in a specific location. Table 2 presents queries related to coronavirus and SARS. It means that people searching for coronavirus and SARS term also searched for these queries. Rising queries are with the highest increase in search frequency since the last time period. Results marked "Breakout" had a tremendous increase, probably because these queries are new and had few (if any) prior searches. Coronavirus related queries are coming not only in English language, but also in Spanish and French. The second approach is to collect the same data, but only for China. Because of the general unavailability of Google in the China, data could be less precise. Figure 2 reveals that Chinese search queries on this disease were concentrated around SARS query in the beginning. The trend has changed on January 22nd, when interest in coronavirus has become greater than interest in SARS. In Table 3 search term popularity is relative to the total number of Google searches performed at a specific time, in a specific location.
China has a strong collective memory of the SARS outbreak in 2003 [25] , which caused an eventual 8,098 cases, resulting in 774 deaths reported in 17 countries, with the majority of cases in China mainland and Hong Kong [26] . The epidemiological similarity between this outbreak and that of SARS is striking. SARS was then traced to animal markets [27] similarly like in case of 2019-nCoV. This could explain, why in China there was greater express of interest in SARS, than in general term coronavirus. However, after January 22nd, volume of interest in coronavirus started to be greater than interest on SARS. Certainly it is connected with rapid release to the public of the genome sequence of the new virus by Chinese virologists [28] .
On Figures 1 and 2 2 values are calculated on a scale from 0 to 100, where 100 is the day with the most popularity as a fraction of total searches in that day, a value of 50 indicates a day which is half as popular. A value of 0 indicates a day where there was not enough data for this term. Table 3 presents data only from 10 Chinese regions. But it is important to stress, that because of general unavailability of Google in China, Chinese people use Baidu for search. That is why data from Google Trends in China is not precise.
Data from GT reveals interest in many countries worldwide. Actually, interest is shown in at least 44 countries, whereas outbreak is currently reported in 14 countries, except China. It confirms, that currently this situation has a global high level of interest.
This communication is a starting point for further analysis of information demand spread across search engines. Currently Google offers Trends service, which acts as a reverse data engineering and allows to collect data on peoples' interest, in this case interest in coronavirus (2019-nCoV) epidemic.