SARS-CoV-2 infections in 165 countries over time

Abstract

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Differentiation of SARS-CoV-2 Variants Using RT-qPCRs by Targeting Recurrent Mutation Sites: A Diagnostic Laboratory Experience from Multi-Center Regional Study, August 2020–December 2021, Poland

“…These data indicate that fewer patients in the first year of the study were diagnosed in the active phase of infection with high viral load (CT < 30) than in the second one; this result seems to be related to the health care burden, delays in diagnosis, and the availability of tests for SARS-CoV-2; however, it may also be due to the fact that SARS-CoV-2 was a new virus in the human population in 2020, so people attributed the initial symptoms of infection to other diseases, and therefore got examined later. A statistically significant majority of the tested samples were from adults ( p < 0.0001) in roughly the same number of each gender, which is consistent with COVID-19 population studies [ 30 , 31 ]. Some papers report that males present an increased risk of severe acute respiratory syndrome infection and higher mortality [ 32 , 33 ].…”

COVID-19 Diagnostics Outside and Inside the National Health Service: A Single Institutional Experience

“…The age structure of people infected with SARS-CoV-2 in this study is quite typical and does not differ from those reported in other populations [5,6]. The relationship between the prevalence and sex is also the same as in other similar studies-women are infected more often [7,8].…”

Proceso electoral durante pandemia COVID-19 en Perú. Incidencia de casos

“…Se deduce que tanto las campañas electorales como las convocatorias a votación presencial conllevarían mayor movilización ciudadana en una época donde el distanciamiento social es crucial. [1,4] Por ello decidimos describir la incidencia estimada de COVID-19 por semanas epidemiológicas nivel nacional (a partir del número de casos de la sala situacional COVID-19 y la población estimada por el Instituto Nacional de Estadística e Informática-INEI para los años 2020 y 2021) para determinar si en el período de campaña electoral y posterior a este hubiera algún cambio en la curva de incidencia estimada a consecuencia de las actividades antes mencionadas.…”

“…En el gráfico 1 se muestra que las fechas de las elecciones se desarrollaron en los picos de incidencia estimada de COVID-19 de la segunda ola de contagios, sin cambios significativos en la curva epidemiológica en las semanas previas o posteriores a las fechas en mención, la tendencia fue similar por regiones y a nivel nacional. Este comportamiento coincide con el de saturación de casos en Perú durante la segunda ola descrita por Louca, [4] en el cual la intervención de cualquier medida de control o contraria no habría afectado el comportamiento esperado de la tendencia epidemiológica de la segunda ola en dicho período. Así existiría un potencial sesgo si se interpreta esta tendencia en puntos de corte de tiempo de forma aislada.…”