key: cord-0867257-7pcik6mf
authors: Chadsuthi, Sudarat; Modchang, Charin
title: Modelling the effectiveness of intervention strategies to control COVID-19 outbreaks and estimating healthcare demand in Germany
date: 2021-04-19
journal: Public Health Pract (Oxf)
DOI: 10.1016/j.puhip.2021.100121
sha: fda6eaa667aeedcefe80bbdd6ad743d1565ad817
doc_id: 867257
cord_uid: 7pcik6mf

OBJECTIVES: An outbreak of the novel coronavirus in December 2019 caused a worldwide pandemic. This disease also impacts European countries, including Germany. Without effective medicines or vaccines, non-pharmaceutical interventions are the best strategy to reduce the number of cases. STUDY DESIGN: A deterministic model was simulated to evaluate the number of infectious and healthcare demand. METHOD: Using an age-structured SEIR model for the COVID-19 transmission, we project the COVID-19–associated demand for hospital and ICU beds within Germany. We estimated the effectiveness of different control measures, including active case-finding and quarantining of asymptomatic persons, self-isolation of people who had contact with an infectious person, and physical distancing, as well as a combination of these control measures. RESULTS: We found that contact tracing could reduce the peak of ICU beds as well as mass testing. The time delay between diagnosis and self-isolation influences the control measures. Physical distancing to limit the contact rate would delay the peak of the outbreak, which results in the demand for ICU beds being below the capacity during the early outbreak. CONCLUSIONS: Our study analyzed several scenarios in order to provide policymakers that face the pandemic of COVID-19 with insights into the different measures available. We highlight that the individuals who have had contact with a virus-positive person must be quarantined as soon as possible to reduce contact with possible infectious cases and to reduce transmission. Keeping physical distance and having fewer contacts should be implemented to prevent overwhelming ICU demand.

In December 2019, the novel coronavirus (severe acute respiratory syndrome 38 coronavirus 2 (SARS-CoV-2)) was first identified in Wuhan, China, and then rapidly spread 39 across the country 1, 2 . The name of the new coronavirus disease was announced as COVID-19 on 40 11 February 2020 by the World Health Organization (WHO). Without natural immunity, this 41 disease has spread worldwide to more than 200 countries and over 3 million cases. In the and active case-finding strategies, the exposed state will become self-quarantine, who had 83 contact with an infectious individual and quarantine themselves before infectiousness ( ) with 84 a probability of self-quarantine ( ), clinical infectious, those who have severe symptoms and 85 need treatment ( ) with a probability of clinical symptoms for age group ( ) and, sub-clinical 86 infectious, who are infectious but do not have any symptoms or have only mild symptoms and 87 do not require treatment ( ). We assumed that the infectious individuals with severe 88 symptoms ( ) will need hospitalization ( ) or critical care in an ICU ( ) with a probability of 89 a clinical case in ICU bed ( ). In this model, ICU cases can either die (D) with a death rate of ICU 90 patients ( ) or be discharged and remained hospitalized (H) until recovery 22 . We assumed that 91 the infectious individuals with severe symptoms will quarantine themselves and go to a 92 hospital, and self-quarantine individuals will quarantine themselves as soon as with delay from 93 exposure to self-isolation ( ). Thus, active case-finding with testing will only look for 94 asymptomatic individuals with positive results that will be isolated in their homes ( ). We 95 assumed that Germany is a closed system and well-mixed with a constant population size of 96 83.5 million 21 . The system of equations for the age group can be described by 135 outbreak. We measured the effectiveness of contact tracing using a time delay from the 136 infectiousness in a person to informing their contacts to be within one or two days ( ).

Physical distancing or social distancing is one of the suggestion scenarios. In this work, we 138 considered different scenarios for reducing contact, such as the duration of the lockdown (less 139 contact), reducing contacts by half, and a cyclic scheduled lockdown 38 . A combination of 140 interventions was considered and proposed to prevent overloading of the medical system.

We first estimated the reproduction number ( 

Assuming that public health agencies have sufficient testing capacity for COVID-19, we getting the testing results, we found the total number of incidences was reduced from baseline 157 for an increasing testing rate. The effectiveness 50% testing rate of a 2-day delay to get the 158 testing results could not reduce the number of cases as well as a 1-day delay, as it caused a 79% beds exceeded the total capacity when the testing less than 20%. Our results suggested that the 170 efficiency of testing has an impact on control measures. Using the best testing parameters, such 171 as 50% of the population and a 1-day delay, the number of ICU beds reduced to about 6,630 172 beds. However, a high testing rate costs a lot of resources. 

We varied the plausible rate of self-isolation from 0.005 to 0.10 (Table 3) . We found that a 1% 181 self-isolation rate 1-day after exposure to an infectious person could reduce the total incidences 182 by 14%. The peak of ICU bed usage dropped below the total capacity 40 when more than 5% of 183 possible exposed individuals' self-isolation 1 day after contact with an infectious person ( 

reducing the transmission and delaying the peak of the outbreak. In this work, we simulated 197 several scenarios (Table 4) , where the epidemic curve and age-specific ICU bed usage are shown 198 in Figure 5 . Our results suggest that only reducing contacts by half for 30 days could delay the 199 peak of ICU beds for 70 days. However, this control measure could reduce the total incidences 200 by only 1.4% of the baseline. Comparing a half lockdown with a full lockdown, we found that the 201 total number of incidences and hospitalization is not different, but a full lockdown could more 202 delay the peak of ICU beds. We also found that cyclic lockdown could reduce the incidence rate 203 more than a single full lockdown. Cyclic lockdowns with an equivalence number of locked-down 204 working days, with either half-lockdowns or full lockdowns for long periods, could delay the 205 peak of infected cases. Our results also suggest that reducing 20% of contacts during the 206 relaxation of a cyclic lockdown could reduce the incidences and delay the peak more than full 207 relaxation. We also considered the curve of ICU bed usage during the early outbreak of some 208 scenarios ( Figure 5 (b) ). Considering the short-term effects, a full lockdown of 150 days is the 209 best strategy to control the demand for health care services. However, a full lockdown for 3 210 months would bring additional problems such as economic and social distress, compared to a 211 cyclic lockdown. 

Thus, our results highlighted testing and self-isolation scenarios with a high rate could 218 reduce the healthcare demand and the total incidence. The physical distancing could only help 219 in delay the peak of the outbreak. Without physical distancing, we estimated the effectiveness of 220 combined testing and self-isolation at reasonable rates (Figure 6 (a) and Supplementary Table   221 1). We found that 5 % of testing rate and 2% of self-isolation could reduce the healthcare 222 demand under the hospital capacity for a 1-day delay. 

There is some evidence suggesting that asymptomatic cases and sub-clinical cases with 244 mild symptoms are potential sources of COVID-19 infection [43] [44] [45] 

(PCR) could provide more accurate results, but this method is more expensive for sample 256 acquisition, preparation, and device operation 47 . However, this strategy can be targeted to high 257 risk groups, such as healthcare workers who are more likely to be exposed to infectious 258 persons 44 and could help end the epidemic 48 . Mass testing could also provide important data to 259 understand the infection dynamics, such as infection rate and duration of symptoms, which 260 could improve the epidemiological models.

We also examined different scenarios of self-isolation of people in contact with an 262 infectious person. Public health officials can promote a self-isolation campaign using a tracing application, such as a mobile application, or manual tracing in order to provide the timing and 264 location where infected cases were found. Self-isolation with contact tracing could help prevent 265 the transmission of the virus by isolating possibly infectious persons before they can spread the 266 disease 5 . We found that a self-isolation rate of only 5% could bring down the peak of ICU bed 267 usage more than mass testing of 10% of the population, as supported by the work of Kucharski 268 and co-worker 49 . However, this strategy is less effective when there is a high rate of 269 transmission before symptom onset 5 . This strategy also requires a suitable system to quickly 

The time delay between diagnosis as infectious and self-isolation influences the 274 effectiveness of these control measures. For example, a 50% testing rate with a 1-day delay 275 could reduce the peak of ICU admission compared to a 2-day delay. 10% of people self-isolating 276 within 24 hours after exposure to an infectious individual could reduce the ICU bed usage peak 277 by twice compared to a 48-hour delay in isolating. Thus, timely testing results and self-isolation 278 should be considered a key method to control the demand for ICU beds.

To delay the peak of the epidemic, we analyzed some scenarios for physical distancing.

Our results suggest that a half lockdown or full lockdown for a short period of time results in a 281 delay of incidences and the ICU peak demand, which is consistent with previous findings 13, 46 .

However, it cannot reduce the peak of incidences as well as active case-finding and self-isolation 283 strategies, when the lockdown was lifted as the number of incidences quickly raised again.

Using a lockdown to suppress COVID-19 will have economic and social costs such as lost jobs.

Another strategy for the lockdown was a cyclic lockdown proposed by Karin and co-worker 38 .

We investigated some cyclic lockdown strategies and compared them with a full lockdown with 

This work has some limitations; our mathematical model did not consider school 294 closures as students may make contact even while schools are closed. As we could not separate the number of imported infected individuals from the number of locally infected individuals, the estimated time-varying reproduction number might not well represent the transmission dynamics in Germany. Our results are based on the parameters of the initial outbreak from the 298 literature of serval countries, which could cause some estimation errors. However, we 299 calibrated the initial parameters with the observed data in Germany. Our models can also be re-300 simulation once updated data is available to more accurately estimate the response.

Our study analyzed several scenarios to control the pandemic of COVID-19 and to 302 inform on how to best affect the situation. Healthcare services must be prepared with sufficient 303 

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This research was supported by the Faculty of Science, Naresuan University, and the 317 National Science and Technology Development Agency, Thailand. We thank Mahidol University