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Table 3 Parameter Estimates, Odds Ratios, and Probabilities for GEE Models

From: Impact of COVID-19 on HIV service delivery in Miami-Dade County: a mixed methods study

 

Est.

Lower

Upper

P-value

ORa

Lower

Upper

Ï€

Lower

Upper

Disruption

 HIV Antibody Testing

0.637

0.302

0.972

p=0.0002

1.89

1.35

2.67

0.372

0.282

0.471

 STI Testing

0.881

0.498

1.264

p<.0001

2.41

1.65

3.54

0.429

0.333

0.530

Innovation

 Sexual/Reprod. Health

0.396

0.017

0.759

p=0.04

1.47

1.02

2.14

0.451

0.352

0.555

 HIV Antibody Testing

0.866

0.451

1.282

p<.0001

2.38

1.57

3.60

0.570

0.470

0.665

 HIV Case Management

0.606

0.272

0.940

p=0.0004

1.83

1.31

2.56

0.506

0.407

0.604

 PrEP Initiation

0.462

0.074

0.850

p=0.0196

1.59

1.08

2.34

0.470

0.372

0.569

 STI Testing

0.454

0.075

0.833

p=0.0188

1.58

1.08

2.30

0.468

0.372

0.566

  1. aThe Odds Ratios compare the statistically significant variables against the disruption and innovation variable with the lowest frequency count (reference), which for the disruption dataset is Antiretroviral Initiation and for the innovation dataset is Laboratory Monitoring for Antiretroviral therapy