Table.

Optimal testing and isolation strategies and price thresholds for cost-effective testing for each potential R_e for SARS-CoV-2 transmission

	Optimal strategy (assuming $5 per test)			Testing threshold (cost per test)
	Testing frequency (days between tests)*	Isolation period	Probability of error
1·1	28	1 week	0·65	$75
1·2	28	1 week	0·66	$125
1·3	14	1 week	0·69	$175
1·4	14	1 week	0·65	$350
1·5	7	1 week	0·72	$325
1·6	7	1 week	0·63	$375
1·7	7	1 week	0·62	$425
1·8	7	1 week	0·62	$475
1·9	7	2 weeks	0·45	$450
2·0	7	2 weeks	0·40	$375
2·1	7	2 weeks	0·40	$350
2·2	7	2 weeks	0·43	$400
2·5	1	2 weeks	0·43	$400
3	1	2 weeks	0·18	$275

The middle columns give the optimal testing and isolation strategies and probability of error for each R_e scenario, assuming that each test costs US$5 and assuming a societal willingness to pay per YLL averted of $100 000. The rightmost column gives a threshold price above which the status-quo strategy (ie, symptom-based testing and isolation) is expected to be more cost-effective than all eight testing strategies considered. The threshold value was identified by assessing all strategies across a range of costs per test up to $2000 at $25 increments. The low transmission and high transmission scenarios in Figure 2, Figure 3 correspond to R_e of 1·2 for low transmission and 2·2 for high transmission. R_e=effective reproduction number. SARS-CoV-2=severe acute respiratory syndrome coronavirus 2. YLLs=years of life lost.

^*A 7-day testing frequency means that individuals are tested once every 7 days, on a rotating basis.