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Quantifying the Regional Disproportionality of COVID-19 Spread: Modeling Study.
Kenji Sasaki1, Yoichi Ikeda1, Takashi Nakano1,2
1Center for Infectious Disease Education and Research, Osaka University, Co-creation BLDG. D88-1, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan, 81 50-5604-3730.
JMIR Formative Research
|January 6, 2025
Summary
The Theil index effectively quantifies regional inequality in COVID-19 spread, identifying disease epicenters. Peaks in the index can signal future case surges, aiding public health interventions.
Area of Science:
- Epidemiology
- Public Health
- Information Theory
Background:
- The COVID-19 pandemic has had profound global health, economic, and social impacts.
- Understanding infectious disease transmission dynamics is crucial for mitigating pandemic consequences.
- The Theil index, a measure of inequality, can identify geographic disparities in disease incidence.
Purpose of the Study:
- To quantify regional disproportionality in infectious disease incidence rates over time.
- To assess the spread of COVID-19 using the Theil index.
- To detect geographic epicenters of disproportionately concentrated COVID-19 cases.
Main Methods:
- Applied the Theil index to daily confirmed COVID-19 case data in the United States over 1100 days.
- Measured relative disproportionality by comparing regional case distributions with population proportions.
- Analyzed variations in regional contributions to the Theil index to track changes in case concentration.
Main Results:
- Observed dynamic patterns of regional disproportionality in COVID-19 cases throughout the pandemic.
- The Theil index reflected a shift from localized outbreaks to widespread transmission.
- Peaks in the Theil index often preceded increases in confirmed COVID-19 cases, indicating potential as an early warning signal.
Conclusions:
- The Theil index is an effective tool for quantifying regional disproportionality in COVID-19 incidence.
- It provides valuable insights for policymakers when used with other indicators like infection and hospitalization rates.
- This approach facilitates efficient monitoring for early intervention and targeted resource allocation.
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