Spatial–temporal trends of COVID-19 infection and mortality in Sudan

Abstract

Since its emergence, the coronavirus disease 2019 (COVID-19), is constantly affecting many parts of the globe and threatening millions of lives worldwide. Charting and aligning disease incidence to identify spatial clustering and patterns continue to be a substantial pathway to understanding disease epidemiology and is essential for implementing effective planning and prevention strategies. A national descriptive study was implemented to present the infection and mortality rates of the COVID-19 pandemic in all states of Sudan. Data were collected and summarized in monthly statistical reports of COVID-19 infection and mortality rates. The reports used were from May 2020 to March 2021. The highest COVID-19 incidence rate occurred in December 2020 with a total incidence of 4863 cases ranging from 0 cases in some of the states to 4164 cases in other states (mean = 270 ± 946, median = 21 cases). Followed by the incidence in May 2020 with a total of 4524 cases ranging from 4 to 3509 cases (mean = 251 ± 794, median = 31 cases). The western and southern states of the country had the lowest mortality rates. While, the middle states (Khartoum and El Gezira) had the highest mortalities. Northern and eastern states had lower mortalities than the middle states, yet, higher than the western states. A strong positive correlation between infection and mortality was found.

Geospatial analysis of sociodemographic factors associated with the first wave of SARS- CoV-2, 6 districts, Zambia, July 2020

“…This nding is consistent with ndings from a study in Namibia that showed that more urban areas had earlier exposure to SARS-CoV-2 and increased transmission rates during waves [6]. Paradoxically, less dense SEAs had a higher prevalence in this study, a nding in contrast to ndings from a study in Nairobi and another study in Sudan [4,5]. This nding could be explained by wealthier urban residential areas with a high prevalence of cases, which are also lower in population density than poorer urban residential areas (e.g., compounds) in Zambia.…”

“…The incidence of SARS-CoV-2 in Africa has been shown to vary by geographic location, with evidence of spatial spread from high-incidence countries to low-incidence neighbouring countries [3]. Increasing population density has been associated with increasing SARS-CoV-2 prevalence in Kenya and Sudan [4,5]. In Namibia, the COVID-19 pandemic began in urban regions and progressively spread to more rural regions.…”

“…As SARS-CoV-2 transmission occurs through exposure to droplets, aerosols, and fomites, the geographic distribution of sociodemographic factors such as urbanicity, socioeconomic status, population density, accessibility to water, sanitation, and hygiene (WASH) could contribute to the geospatial spreading patterns of SARS-CoV-2 in Zambia [3][4][5]. The incidence of SARS-CoV-2 in Africa has been shown to vary by geographic location, with evidence of spatial spread from high-incidence countries to low-incidence neighbouring countries [3].…”