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Modern Geomatics Technologies and Applications

With the temporal neighborhood increasing to three days, parts of Australia and Brazil have been identified
as historic cold spots and western China as oscillating cold spots (Fig. 3.a). Also, by setting the temporal
neighborhood to 14 days, the results of Fig. 3.b were obtained. According to the results, many parts of the southern
hemisphere were identified as persistent cold spots due to their low confirmed cases.

Countries like Mexico have a new hot spot in the northern part of the neighborhood with the USA and a
historic cold spot in the southern part of the neighborhood with Guatemala. New hot spots have also been found in
southern Canada and oscillating hot spots in eastern China. Figure 2.c shows an example of the patterns produced
for death, with a neighboring step of 1 day.
According to WHO reports, the official estimated range for COVID-19 has been 2 to 14 days. Therefore, the
hot/cold spot map for confirmed cases and deaths was prepared by setting the temporal neighborhood steps at 1,3,7
and 14 days. In terms of infections, large parts of Europe, Middle East, the USA, South Korea and the East of China

have been identified as hot patterns. However, in terms of death rates, parts of Europe, particularly Italy, France,
Spain, the United Kingdom, and the Netherlands, have also been identified as oscillating hot spots. Parts of the
United States have been reported as a new hot spot due to increased deaths and parts of China as a persistent cold
spot due to reduced deaths.
The results of the maps are presented in Table 2. For each map, the percentages of areas in the different types

of hot spots and cold spots were obtained. With increasing temporal neighborhood steps, the percentage of no
patterns decreased and the hot/cold patterns increased. Fortunately, for now, the percentage of cold spots is higher
than hot spots. In addition, p-value, z-scores, hot percent, and cold percent were calculated for each pixel. Hot and
cold percentages are high and low values percentages, respectively. The highest z-score was for cases in Spain and
deaths in Italy and Iran, indicating more intense hot spots. The lowest z-score was for cases in Madagascar and
deaths in Gabon, indicating more intense cold spots. It is clear that the results of spatio-temporal analysis show the
hot/cold spot areas with more detail.

4. Conclusion
Epidemiology is a study and analysis of distribution patterns and situations of disease in the study area

[15,16]. With the daily increase of COVID-19 cases, studying its patterns in different regions and discovering
Spatio-temporal clusters is needed. By analyzing hot/cold spots and finding high-risk areas, it is possible to find
ways to reduce its spread. It is also important to predict the number of cases and deaths because of the lack of potent
drugs against Coronavirus infection and its abundant rise. Accurate prediction of cases and deaths can greatly assist
politicians and decision-makers in legislating until its vaccine is discovered that suggest for further research. Also,
effective factors in COVID-19 will be extracted which is suggests further study in this field.