# To Swab or Not to Swab? The Lesson Learned in Italy in the Early Stage of the COVID-19 Pandemic
## 4 Discussion  
The present work reports an analysis of the impact on the unfolding of COVID-19 in two Italian regions in the North of the country, which was heavily affected by the pandemic outbreak, resulting from opposite testing strategies. Veneto implemented extensive testing of mild symptomatic individuals along with the contacts of infected patients. Contrariwise, Piemonte limited the testing to individuals with severe respiratory symptoms, according to the first recommendations of the Ministry of Health and the Higher Health Council. In this work, the daily time series of hospitalizations was considered. A prediction model was developed using data from Veneto. The results suggest that the cumulative number of COVID-19 cases observed is not suitable alone to predict the hospitalization trend. The same model largely underestimated the number of hospitalizations in Piemonte, which despite a similar number of positive cases, had a higher number of hospitalizations than Veneto, notwithstanding the similar age structures of the population in the two regions. Figure 1: **(A)**: Predicted trend of COVID-19 hospitalizations in Piemonte (red solid line) based on Veneto daily cumulative number of COVID-19 positive cases. Observed hospitalizations are reported as red points in Piemonte and blue points in Veneto; **(B)**: predicted trend of hospitalizations in Piemonte (red solid line) based on daily cumulative number of COVID-19 positive cases in Veneto and the number of swabs performed. The two population also share a similar prevalence of comorbidities like diabetes, which is associated with severe COVID-19 and thus hospitalization as consequences [14,15]. In searching for a potential explanation of the observed differences in the number of hospitalizations between the two regions, the best fitting model included the number of swabs and a time-interaction. This second model was also able to predict the observed trend over time in Piemonte. The percentage of the expected error dropped from 70% of the first simpler model to 15%. Using the model developed on data from Veneto to predict hospitalizations in Piemonte allowed us to assess whether the lack of an extensive testing strategy in Piemonte could explain the quicker progression of the hospitalizations. Adjusting by the number of swabs largely explained the difference between the observed hospitalizations in Piemonte and the expected ones if the same testing strategy of Veneto would have been adopted, pointing out that more testing in Piemonte could have reduced the number of hospitalizations. Veneto was one of the first Italian regions affected by the COVID-19 epidemic; at the same time, it was among the first regions to experience a reduction in COVID-19 hospitalizations due to the early implementation of containment policies [16] and a broad-spectrum testing strategy [6]. The proactive strategy adopted in Veneto was a key component to ensure a prompt surveillance system, especially in the presence of asymptomatic cases and mildly symptomatic cases. Identifying early cases allowed their isolation, even if they were asymptomatic, and enhanced the ability to provide home care assistance as soon as they manifested the symptoms, reducing the burden of hospitals [6]. This observation is strengthened by the number of positive cases in Piemonte, which exceeded by only 30% the total number of hospitalizations during the first three weeks of the pandemic. On the contrary, in Veneto, after the first week, the number of positive cases was already more than three times the number of hospitalizations. Hence, in the first period of the pandemic, most likely due to the lack of more widespread testing, in Piemonte many cases were tested because they presented to the hospital with severe respiratory symptoms only. The analysis was limited to two weeks after the hospitalization trend started in order to differentiate between the two regions. This choice was twofold: first, in April in Piemonte, the number of swabs processed started to increase progressively.