In every country except China, COVID-19 first infection cases were imported by travelers, which are either people coming back to their own country or visiting foreigners (international or external tourists). In a global and regional phenomenological analysis of COVID-19 spread, we assume that tourism inflow is a trigger mechanism of worldwide dissemination at the pandemic onset days. Taking into account all countries, a convenient common-time origin timeline was employed as if the beginning of the epidemic would have occurred simultaneously in every country. We obtained very good statistical Pearson and Spearman correlations between accumulated infected cases by country and a positive power of the product [Formula: see text], where [Formula: see text] is the tourism inflow before the pandemic and [Formula: see text] is the country population.

In the USA, COVID-19 first infection cases were imported by external travelers. At the epidemic onset days, we assume that the disease partially spreads due to domestic passengers air transportation in its densely connected airport network. Taking into account all USA states, we arranged COVID-19 infected cases data in a convenient common time origin timeline as if the beginning of the epidemic would have occurred simultaneously in every state. Looking for a trend between cases and air passengers, we obtained with this timeline very good statistical Pearson and Spearman correlations between accumulated infected cases by state and a positive power of the product [Formula: see text], where [Formula: see text] is the domestic flight passengers (travelers) inflow by state before the epidemic and [Formula: see text] is its population. We also found a good correlation between percentages of urban area by state and their COVID-19 daily new cases growth rates at onset days.

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From the years 2001 to 2017, per capita nominal and real (adjusted to inflation) GDP at purchasing power parity (PCGDP-PPP) distributions for cities and regions are fitted to various functions. For most years and regions, real PCGDP-PPP data are very well adjusted to the one-parameter Boltzmann–Gibbs distribution (BGD), in accordance with the exponential behavior predicted by the simple econophysics analogy between conserved money in economic trade and energy in elastic collisions in gases. Overall, fittings are better for large regions in recent years, which may reflect an increasing economic globalization in time. Cities, small regions and large regions values are well fitted by stretched exponential distributions.

Remittances, as money or goods that people send to families and friends, are very important social and economic phenomenon at local, national, regional and international levels. In the year 2017, total international remittances were at levels around USD 613 billion. From World Bank bilateral remittances and migration matrixes, we calculate for each country and territory its aggregated or total amount of remittances inflow (TRI) coming from the rest of the world, its total remittances outflow (TRO) extracted from that country and sent to all other countries, its total emigrant stock (TEMI) living overseas, and its total number of foreign-world immigrants (TIMM) living in that country. For each of these quantities, its highest-ranked countries follow an approximate Pareto power law distribution. Remittances and migrants flow in opposite directions, the statistical correlation [Formula: see text] between TRI and TEMI is 0.79, and between TRO and TIMM is 0.97. Both inflowing remittances per emigrant TRI/TEMI and outflowing remittances per immigrant TRO/TIMM fluctuate approximately around 3100 USD per year.