Risk analysis and hot spots detection of SARS-CoV-2 in Nigeria using demographic and environmental variables: an early assessment of transmission dynamics

Yaro, Clement Ameh; Eneche, P; Anyebe, Daniel

doi:10.1080/09603123.2020.1834080

Cited by 6 publications

(3 citation statements)

References 46 publications

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“…Coronaviruses are a large group of viruses, some of which can cause respiratory diseases in humans and often trigger serious global public health crises. The coronavirus (CoV) belongs to the family Coronaviridae and is a single-stranded envelope virus with an RNA genome size of approximately 26–32 kb 3 . SARS-CoV-2 can be transmitted from person to person through droplets, aerosols, and contact 4 .…”

Section: Introductionmentioning

confidence: 99%

“…Among numerous niche models, MaxEnt has been widely used due to its advantages 44 , 45 . It has been widely used in many diseases, including COVID-19 3 , 46 , 47 . To overcome the above shortcomings, the purpose of this study is to conduct a comprehensive analysis based on geographically narrow data sources, use the MaxEnt model to assess the collective impact of the above factors on COVID-19 cases, and further explore the differences in these impacts in different regions.…”

Section: Introductionmentioning

confidence: 99%

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Assessing eco-geographic influences on COVID-19 transmission: a global analysis

Pan,

Villalan,

et al. 2024

Sci Rep

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COVID-19 has been massively transmitted for almost 3 years, and its multiple variants have caused serious health problems and an economic crisis. Our goal was to identify the influencing factors that reduce the threshold of disease transmission and to analyze the epidemiological patterns of COVID-19. This study served as an early assessment of the epidemiological characteristics of COVID-19 using the MaxEnt species distribution algorithm using the maximum entropy model. The transmission of COVID-19 was evaluated based on human factors and environmental variables, including climate, terrain and vegetation, along with COVID-19 daily confirmed case location data. The results of the SDM model indicate that population density was the major factor influencing the spread of COVID-19. Altitude, land cover and climatic factor showed low impact. We identified a set of practical, high-resolution, multi-factor-based maximum entropy ecological niche risk prediction systems to assess the transmission risk of the COVID-19 epidemic globally. This study provided a comprehensive analysis of various factors influencing the transmission of COVID-19, incorporating both human and environmental variables. These findings emphasize the role of different types of influencing variables in disease transmission, which could have implications for global health regulations and preparedness strategies for future outbreaks.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessing eco-geographic influences on COVID-19 transmission: a global analysis

Pan,

Villalan,

et al. 2024

Sci Rep

View full text Add to dashboard Cite

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“…Therefore, these numbers are very likely an underestimation of the true picture of the COVID-19 burden globally, and in Nigeria. Notably, Southern Nigeria has been categorized as a high-risk zone for SARS-CoV-2 transmission [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Detection of SARS-CoV-2 in Terrestrial Animals in Southern Nigeria: Potential Cases of Reverse Zoonosis

Happi,

Ayinla,

Ogunsanya

et al. 2023

Viruses

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Since SARS-CoV-2 caused the COVID-19 pandemic, records have suggested the occurrence of reverse zoonosis of pets and farm animals in contact with SARS-CoV-2-positive humans in the Occident. However, there is little information on the spread of the virus among animals in contact with humans in Africa. Therefore, this study aimed to investigate the occurrence of SARS-CoV-2 in various animals in Nigeria. Overall, 791 animals from Ebonyi, Ogun, Ondo, and Oyo States, Nigeria were screened for SARS-CoV-2 using RT-qPCR (n = 364) and IgG ELISA (n = 654). SARS-CoV-2 positivity rates were 45.9% (RT-qPCR) and 1.4% (ELISA). SARS-CoV-2 RNA was detected in almost all animal taxa and sampling locations except Oyo State. SARS-CoV-2 IgGs were detected only in goats from Ebonyi and pigs from Ogun States. Overall, SARS-CoV-2 infectivity rates were higher in 2021 than in 2022. Our study highlights the ability of the virus to infect various animals. It presents the first report of natural SARS-CoV-2 infection in poultry, pigs, domestic ruminants, and lizards. The close human–animal interactions in these settings suggest ongoing reverse zoonosis, highlighting the role of behavioral factors of transmission and the potential for SARS-CoV-2 to spread among animals. These underscore the importance of continuous monitoring to detect and intervene in any eventual upsurge.

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Gaps and Opportunities for Data Systems and Economics to Support Priority Setting for Climate-Sensitive Infectious Diseases in Sub-Saharan Africa: A Rapid Scoping Review

Delight,

Brunn,

Ruiz

et al. 2024

Preprint

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Climate change alters risks associated with climate-sensitive infectious diseases (CSIDs) with pandemic potential. This poses additional threats to already vulnerable populations, further amplified by intersecting social factors, such as gender and socioeconomic status. Currently, critical evidence gaps and inadequate institutional and governance mechanisms impact on the ability for African States to prevent, detect and respond to CSIDs. The aim of this study was to explore the role of data systems and economics to support priority setting for CSID preparedness in sub-Saharan Africa. We conducted a rapid scoping review to identify existing knowledge and gaps relevant to economics and data systems. A literature search was performed across six bibliographic databases in November 2023. A list of 14 target pathogens, identified by the World Health Organization as Public Health Emergencies of International Concern or R&D Blueprint Pathogens, was adopted and compared to a database of CSIDs to determine relevant inclusion criteria. Extracted data were synthesised using bibliometric analysis, thematic topic categorisation, and narrative synthesis to identify research needs, evidence gaps, and opportunities for priority setting. We identified 68 relevant studies. While African author involvement has been increasing since 2010, few studies were led by senior authors from African institutions. Data system studies (n = 50) showed broad coverage across CSIDs and the WHO AFRO region but also a high degree of heterogeneity, indicating a lack of clearly defined standards for data systems related to pandemic preparedness. Economic studies (n = 18) primarily focused on COVID-19 and Ebola and mostly originated from South Africa. Both data system and economic studies identified limited data sharing across sectors and showed a notable absence of gender sensitivity analyses. These significant gaps highlight important opportunities to support priority setting and decision-making for pandemic preparedness, ultimately leading to more equitable health outcomes.

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Risk analysis and hot spots detection of SARS-CoV-2 in Nigeria using demographic and environmental variables: an early assessment of transmission dynamics

Cited by 6 publications

References 46 publications

Assessing eco-geographic influences on COVID-19 transmission: a global analysis

Assessing eco-geographic influences on COVID-19 transmission: a global analysis

Detection of SARS-CoV-2 in Terrestrial Animals in Southern Nigeria: Potential Cases of Reverse Zoonosis

Gaps and Opportunities for Data Systems and Economics to Support Priority Setting for Climate-Sensitive Infectious Diseases in Sub-Saharan Africa: A Rapid Scoping Review

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