Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019–2020 Flu Season: A Retrospective Longitudinal Study
Abstract
:1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Season | Number of Visits | Rate per 1000 | Percentage Change in Rates Comparing 2019–2020 to Previous Seasons | Number of Visits | Rate per 1000 | Percentage Change in Rates Comparing 2019–2020 to Previous Seasons | Number of Visits | Rate per 1000 | Percentage Change in Rates Comparing 2019–2020 to Previous Seasons |
---|---|---|---|---|---|---|---|---|---|
COVID-like symptoms | California | Texas | Florida | ||||||
2015–2016 | 4134 | 45 | −29% *** | 3209 | 50 | −23% *** | 3569 | 48 | −26% *** |
2016–2017 | 4970 | 51 | −19% ** | 3525 | 51 | −22% *** | 4421 | 53 | −18% ** |
2017–2018 | 5058 | 51 | −19% ** | 4176 | 60 | −8% ** | 4370 | 52 | −20% *** |
2018–2019 | 4838 | 51 | −19% ** | 4219 | 62 | −5% * | 4340 | 53 | −18% ** |
4-season Average | 4750 | 49 | −22% ** | 3782 | 56 | −14% *** | 4175 | 52 | −20% *** |
2019–2020 * | 5388 | 63 | 4132 | 65 | 4956 | 65 | |||
Influenza | California | Texas | Florida | ||||||
2015–2016 | 196 | 2 | −71% ** | 102 | 2 | −82% *** | 162 | 2 | −71% *** |
2016–2017 | 308 | 3 | −57% ** | 242 | 3 | −73% *** | 254 | 3 | −57% *** |
2017–2018 | 973 | 10 | 43% | 1185 | 17 | 55% | 944 | 11 | 57% |
2018–2019 | 216 | 2 | −71% ** | 243 | 4 | −64% ** | 275 | 3 | −57% ** |
4-season average | 423 | 4 | −43% * | 443 | 6 | −65% * | 411 | 5 | −29% |
2019–2020 | 596 | 7 | 683 | 11 | 541 | 7 | |||
Non-influenza ILI | California | Texas | Florida | ||||||
2015–2016 | 7528 | 81 | 7% | 5243 | 81 | −9% | 5799 | 78 | −7% |
2016–2017 | 8004 | 81 | 7% | 5923 | 85 | −4% | 7658 | 92 | 10% |
2017–2018 | 8696 | 88 | 16% | 7294 | 105 | 18% * | 7909 | 94 | 12% |
2018–2019 | 6684 | 71 | −7% | 6187 | 92 | 3% | 7066 | 86 | 2% |
4-season average | 7728 | 80 | 5% | 6162 | 91 | 2% | 7108 | 88 | 5% |
2019–2020 | 6528 | 76 | 5641 | 89 | 6478 | 84 |
Season (Ref 2019–2020) | Adjusted Risk Ratio | Adjusted Risk Ratio | Adjusted Risk Ratio |
---|---|---|---|
CA COVID-Like Symptoms | TX COVID-Like Symptoms | FL COVID-Like Symptoms | |
2015–2016 | 0.72 *** (0.69–0.75) | 0.75 *** (0.72–0.79) | 0.72 *** (0.69–0.75) |
2016–2017 | 0.81 *** (0.78–0.85) | 0.77 *** (0.73–0.81) | 0.79 *** (0.76–0.82) |
2017–2018 | 0.80 *** (0.77–0.84) | 0.89 *** (0.85–0.93) | 0.83 *** (0.80–0.87) |
2018–2019 | 0.82 *** (0.79–0.86) | 0.93 *** (0.89–0.97) | 0.81 *** (0.78–0.84) |
Season (Ref 2019–2020) | CA Influenza diagnoses | TX Influenza diagnoses | FL Influenza diagnoses |
2015–2016 | 0.29 *** (0.24–0.34) | 0.15 *** (012–0.19) | 0.35 *** (0.30–0.42) |
2016–2017 | 0.45 *** (0.39–0.52) | 0.32 *** (0.27–0.37) | 0.43 ** (0.37–0.50) |
2017–2018 | 1.24 ** (1.11–1.38) | 1.46 *** (1.32–1.62) | 1.51 ** (1.36–1.68) |
2018–2019 | 0.34 *** (0.29–0.40) | 0.35 *** (0.30–0.40) | 0.50 *** (0.43–0.57) |
Season (Ref 2019–2020) | CA non-influenza ILI diagnoses | TX non-influenza ILI diagnoses | FL non-influenza ILI diagnoses |
2015–2016 | 1.04 * (1.00–1.08) | 0.93 *** (0.90–0.97) | 0.92 *** (0.89–0.96) |
2016–2017 | 1.05 * (1.01–1.09) | 1.10 (1.06–1.17) | 1.07 *** (1.04–1.11) |
2017–2018 | 1.08 *** (0.004–0.009) | 1.10 *** (1.06–1.14) | 1.06 ** (1.02–1.09) |
2018–2019 | 0.91 *** (0.88–0.94) | 1.01 (0.97–1.05) | 0.99 (0.96–1.02) |
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Lukowsky, L.R.; Der-Martirosian, C.; Steers, W.N.; Kamble, K.S.; Dobalian, A. Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019–2020 Flu Season: A Retrospective Longitudinal Study. Viruses 2022, 14, 200. https://doi.org/10.3390/v14020200
Lukowsky LR, Der-Martirosian C, Steers WN, Kamble KS, Dobalian A. Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019–2020 Flu Season: A Retrospective Longitudinal Study. Viruses. 2022; 14(2):200. https://doi.org/10.3390/v14020200
Chicago/Turabian StyleLukowsky, Lilia R., Claudia Der-Martirosian, William Neil Steers, Kiran S. Kamble, and Aram Dobalian. 2022. "Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019–2020 Flu Season: A Retrospective Longitudinal Study" Viruses 14, no. 2: 200. https://doi.org/10.3390/v14020200