This chart shows the evolution over time of the daily COVID-19 cases in absolute numbers across UN subregions. To remove intra-week volatility in the reported data, the indicator is transformed into a 7-day trailing average (the average value of the latest observation and the preceding 6 days).
The absolute expression of cases is useful to highlight the the contribution of countries or groups of countries to the global total. In contrast, case rates, which express the absolute number of cases relative to population size, provide an indication of performance controlling for population size.
It should be noted that the different regional groups shown here are of very different population size dimensions. In light of these differences in population size, we expect large differences in absolute case numbers even if case rates were constant across groups.
Finally, note that limitations to testing will mean that the number of confirmed cases is lower than the true number of infections.
Pandem-ic uses the World Bank income classification as a major building block in the analysis of the impact of the pandemic.
The income classification groups countries in four buckets by per capita income levels: high-income countries (HICs), upper-middle-income countries (UMICs), lower-middle-income countries (LMICs) and low-income countries (LICs). We use the current FY2022 classification, which determines the thresholds of the buckets as follows:
See here for a dynamic visualization of how the income classification of countries has changed over time through the current FY2022 classification
A good part of this site also analyzes the pandemic by region (where we use the World Bank regional classification and the UN geo-scheme of subregions). In both cases (i.e. across income groups and regions), the universe of countries is based on the World Bank income classification. More on that in the next note.
The universe of countries on this website is determined as follows.
Note that the vaccination data is pulled from Our World in Data, which utilizes a slightly different universe of locations. In sticking with the above 196 countries and economies, we have made the following adjustments relative to the OWID universe.
For each of the above adjustments to the vaccination data, we make adjustments to the demographic data that vaccine information is related to (including population size, age structure and priority group size).
Finally, note that no adjustments are required to the totals for France as its overseas territories and dependencies are already included.