Evaluation of the effectiveness of surveillance policies to control the COVID-19 pandemic in São Paulo, Brazil

Table 3 Estimated Coefficients for the Segmented Regression for Genomic Surveillance Policies in São Paulo State (Brazil)¹

Dependent Variables of RT-PCR Testing Outcome:	I. Number of samples		II. Time delay between sample collection and deposit to the GISAID
	Coefficient	Newey Standard Error	Coefficient	Newey Standard Error
Intercept	0.730	(0.443)	56.687	(2.481)***
Time	0.138	(0.033)**	− 0.155	(0.141)
Testing Policy IV	− 4.731	(1.582)**	7.509	(6.794)
Time*Post Testing Policy IV	− 0.158	(0.037)***	0.184	(0.170)
Post intervention linear trend
Testing Policy IV (β1 + β3)	− 0.020	(0.012)	0.028	(0.081)
Number of Epidemiological Weeks		23		23

From December 27, 2020 to July 05, 2021¹ (aggregated data by week)
For each dependent variable, the following segmented regression model was estimated: Y_t = β0 + β1 time + β2Testing Policy IV_t + β3 time*post Testing Policy IV_t + ε_t
***p-value < 0.001, **p-value < 0.05, *p-value < 0.1

ISSN: 2397-0642