Nowcasting and forecasting provincial-level SARS-CoV-2 case positivity using google search data in South Africa

Nsoesie, Elaine O.; Sy, Karla Therese L; Oladeji, Olubusola; Sefala, Raesetje; Nichols, Brooke E

doi:10.1101/2020.11.04.20226092

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…However, the local context is important in both research and interpretation of findings. Search terms commonly associated with specific infectious diseases (such as, influenza or COVID-19) in western countries might not be associated with those diseases in sub-Saharan African countries 35 . For example: ginger, lemon, malaria, and AIDS were shown to be associated with ILI in Cameroon, where this is likely not ne the case in western countries.…”

Section: Discussionmentioning

confidence: 99%

Forecasting influenza-like illness trends in Cameroon using Google Search Data

Nsoesie

Oladeji

Abah

et al. 2021

Sci Rep

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Although acute respiratory infections are a leading cause of mortality in sub-Saharan Africa, surveillance of diseases such as influenza is mostly neglected. Evaluating the usefulness of influenza-like illness (ILI) surveillance systems and developing approaches for forecasting future trends is important for pandemic preparedness. We applied and compared a range of robust statistical and machine learning models including random forest (RF) regression, support vector machines (SVM) regression, multivariable linear regression and ARIMA models to forecast 2012 to 2018 trends of reported ILI cases in Cameroon, using Google searches for influenza symptoms, treatments, natural or traditional remedies as well as, infectious diseases with a high burden (i.e., AIDS, malaria, tuberculosis). The R2 and RMSE (Root Mean Squared Error) were statistically similar across most of the methods, however, RF and SVM had the highest average R2 (0.78 and 0.88, respectively) for predicting ILI per 100,000 persons at the country level. This study demonstrates the need for developing contextualized approaches when using digital data for disease surveillance and the usefulness of search data for monitoring ILI in sub-Saharan African countries.

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Section: Discussionmentioning

confidence: 99%

Forecasting influenza-like illness trends in Cameroon using Google Search Data

Nsoesie

Oladeji

Abah

et al. 2021

Sci Rep

Self Cite

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“…Ssentongo et al provide a set of forecasts for SARS-CoV-2 on the African continent. As more models are assembled for the continent (10)(11)(12), new pathways open to evaluate combinations of predictions to strengthen forecasting nationally and at larger scales. Forecasts tell us one important part of the policy landscape: Simply knowing whether case numbers are increasing or decreasing (Fig.…”

mentioning

confidence: 99%

“…Ssentongo et al provide a set of forecasts for SARS-CoV-2 on the African continent. As more models are assembled for the continent ( 10 – 12 ), new pathways open to evaluate combinations of predictions to strengthen forecasting nationally and at larger scales.…”

mentioning

confidence: 99%

Building toward useful SARS-CoV-2 models in Africa

Archibong

Metcalf

2021

Proc. Natl. Acad. Sci. U.S.A.

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Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

Clark,

Neumann,

Hopkins

et al. 2024

JMIR Public Health Surveill

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Background Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts. Objective This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods. Methods A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers. Results Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses. Conclusions The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.

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Nowcasting and forecasting provincial-level SARS-CoV-2 case positivity using google search data in South Africa

Cited by 4 publications

References 13 publications

Forecasting influenza-like illness trends in Cameroon using Google Search Data

Forecasting influenza-like illness trends in Cameroon using Google Search Data

Building toward useful SARS-CoV-2 models in Africa

Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

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