This study provides a phenomenological method to describe the exponential growth, saturation and decay of coronavirus disease 2019 (COVID-19) deaths and infections via a Monte Carlo approach. The calculations connect Gompertz-type trial distributions of infected people per day with the distribution of deaths adopting two gamma distributions to account for the elapsed time that encompass the incubation and symptom onset to death periods. The analyses include death's data from United States of America (USA), Brazil, Mexico, United Kingdom (UK), India and Russia, which comprise the four countries with the highest number of deaths and the four countries with the highest number of confirmed cases, as of Aug 07, 2020, according to the World Health Organization webpage: https://covid19.who.int/table. The Gompertz functions were fitted to the data of weekly averaged confirmed deaths per day by mapping the χ 2 values. The uncertainties, variances and covariances of the model parameters were calculated by propagation, taking into account the standard deviations of the data for each epidemiological week. The fitted functions for the average deaths per day for USA and India have an upward trend, with the former having a higher growth rate and quite huge uncertainties. For Mexico, UK and Russia, the fits are consistent with a slope down pattern. For Brazil we found a subtle trend down, but with significant uncertainties. The USA, UK and India data shown a first peak with a higher growth rate when compared to the second one (typically 2.7 to 3.7 times higher), demonstrating the benefits of non-pharmaceutical interventions of sanitary measures and social distance flattening the curves of the pandemic. For the case of USA, however, a third peak seems quite plausible, most likely related with the recent relaxation policies. Brazil's data are satisfactorily described by two highly overlapped Gompertz functions with similar growth rates, suggesting a two-steps process for the pandemic spreading. For the case of Mexico and Russia single peaks with smoother slopes fitted the data satisfactorily. The 95% confidence intervals for the total number of deaths (×10 3 ) predicted by the model for Aug 31, 2020 are 160 to 220, 110 to 130, 59 to 62, 46.6 to 47.3, 54 to 63 and 16.0 to 16.7 for USA, Brazil, Mexico, UK, India and Russia, respectively. Our estimates for the prevalences of infections are in reasonable agreement with some preliminary reports from serological studies carried out in USA and Brazil. The prevalences and 95% confidence intervals for Aug 1, 2020 were estimated to be 8.