Of course, this is not the first global epidemic and it will not be the last. Humans have experienced four global epidemics throughout history, if they are Black Death (14th Century), Spanish influenza (1918), The global epidemics of HIV / AIDS (20th century), and SARS (2002–2003) have affected many parts of the world. Covid-19 stands out because of such high international tours. It spread rapidly around the world at an unexpected time and as a result, many countries have completely shut it down. At the time of writing(07/06/2021), more than 173 million Covid-19 patients have been reported worldwide and more than 3.7 million have died. Covid-19 is also different from previous epidemics.

What sort of measures are required to contain the spread of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19)? The rich data from the Open COVID-19 Data Working Group include the dates when people first reported symptoms, not just a positive test date. Using these data and real-time travel data from the internet services company Baidu, Kraemer et al. found that mobility statistics offered a precise record of the spread of SARS-CoV-2 among the cities of China at the start of 2020. The frequency of introductions from Wuhan were predictive of the size of the epidemic sparked in other provinces. However, once the virus had escaped Wuhan, strict local control measures such as social isolation and hygiene, rather than long-distance travel restrictions, played the largest part in controlling SARS-CoV-2 spread.

South Korea, a country of 50 million people, has set an example of successfully flattening the curve of new COVID-19 infections by conducting over 400,000 tests [13] (Figure 2). This was achieved by setting up drive-through testing, allowing at least 10,000 people to be tested per day. South Korea's foreign minister Kang Kyung-wha, in an interview with BBC News [2], said that "Testing is central because that leads to early detection, minimizes further spread, and quickly treats those found with the virus". Several countries are suffering from severe community spread because of their delays in testing [12], two of the prime examples being the United States and Italy. In the United States, among a population of 330 million, the number of confirmed cases is more than 230,000 with over 10,000 deaths and these numbers are growing exponentially (Figure 3), whereas in South Korea there are around 9976 confirmed cases and 169 deaths (as of April 2, 2020). Thus, early testing and repeated testing at regular intervals are two of the key strategies to ensure a low fatality rate. However, for countries with a large population (more than 100 million), it is difficult to adopt exhaustive testing schemes because of the limited number of available testing-kits and facilities. Testing a lot of people with mild or no symptoms would occupy the limited testing resources, which could otherwise be used for highrisk patients. However, it is also important to test individuals with mild or no symptoms to detect asymptomatic cases [10] and implement a method that systematically tests individuals for COVID-19.

Tour recommendation and itinerary planning are challenging tasks for tourists, due to their need to select Points of Interest (POI) to visit in unfamiliar cities, and to select POIs that align with their interest preferences and trip constraints. We propose an algorithm called PersTour for recommending personalized tours using POI popularity and user interest preferences, which are automatically derived from real-life travel sequences based on geo-tagged photos. Our tour recommendation problem is modelled using a formulation of the Orienteering problem, and considers user trip constraints such as time limits and the need to start and end at specific POIs. In our work, we also reflect levels of user interest based on visit durations, and demonstrate how POI visit duration can be personalized using this time-based user interest. Using a Flickr dataset of four cities, our experiments show the effectiveness of PersTour against various baselines, in terms of tour popularity, interest, recall, precision and F1-score. In particular, our results show the merits of using time-based user interest and personalized POI visit durations, compared to the current practice of using frequency-based user interest and average visit durations.