Time Series Analysis of Google Online Search Trends and Reported Cases of HIV in Nigeria

The HIV epidemic in Nigeria remains a significant public health challenge, with reported cases rising despite control efforts. Understanding public interest in HIV-related topics through online search trends can provide valuable insights for monitoring and forecasting HIV trends. This study explores the relationship between online search trends for HIV-related terms and reported HIV cases in Nigeria from 2004 to 2023. Using Google Trends and UNAIDS databases, the study found significant correlations between online search trends and reported HIV cases, highlighting the potential of Google Trends data for monitoring public interest. However, time series forecasting revealed that Google Trends data did not significantly predict HIV case reports, suggesting its limitations as a predictive tool. Overall, online search trends reflect public interest in HIV-related topics but may not directly predict actual HIV prevalence in Nigeria.

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Publication Details

Journal
International STD Research & Reviews
Published
2025-04-14
DOI
https://doi.org/10.9734/isrr/2025/v14i1187
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
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article

Time Series Analysis of Google Online Search Trends and Reported Cases of HIV in Nigeria

Okabeonye Sunday Agbo, Enibokun Theresa Orobator, Vivian Ukamaka Nwokedi, Caleb Otabil et al.
International STD Research & Reviews
Data-Driven Disease Surveillance
article

Time Series Analysis of Google Online Search Trends and Reported Cases of HIV in Nigeria

Okabeonye Sunday Agbo, Enibokun Theresa Orobator, Vivian Ukamaka Nwokedi, Caleb Otabil, Nichodemus Chinedu Nnamani, Maryann Chinyere Ikeagwu
article en

Abstract

The HIV epidemic in Nigeria remains a significant public health challenge, with reported cases rising despite control efforts. Understanding public interest in HIV-related topics through online search trends can provide valuable insights for monitoring and forecasting HIV trends. This study explores the relationship between online search trends for HIV-related terms and reported HIV cases in Nigeria from 2004 to 2023. Using Google Trends and UNAIDS databases, the study found significant correlations between online search trends and reported HIV cases, highlighting the potential of Google Trends data for monitoring public interest. However, time series forecasting revealed that Google Trends data did not significantly predict HIV case reports, suggesting its limitations as a predictive tool. Overall, online search trends reflect public interest in HIV-related topics but may not directly predict actual HIV prevalence in Nigeria.

International STD Research & ReviewsVol. 14(1)
Openalex Percentile: Top 89%
Data-Driven Disease Surveillance
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