key: cord-0869228-rfpmq0t3 authors: Valiati, N. C. M.; Villela, D. A. M. title: Mitigation policies and vaccination in the COVID-19 pandemic: a modelling study date: 2021-01-31 journal: nan DOI: 10.1101/2021.01.27.21250651 sha: 674063b1c1000fc36a760219f36a250f4c49dc57 doc_id: 869228 cord_uid: rfpmq0t3 The perspective of vaccination to protect human population from infection of SARS-CoV-2 virus has great potential to control the pandemic. Nevertheless, vaccine planning requires phased introduction with age groups, health workers, and vulnerable people. We developed a mathematical model capable of capturing the dynamics of the SARS-CoV-2 dissemination aligned with social distancing, isolation measures, and vaccination. The city of Rio de Janeiro provides a case study to analyze possible scenarios including non--pharmaceutical interventions and vaccination in the epidemic scenario. Our results shows that a combination of different policies such as case isolation and social distancing are more effective for mitigating the epidemics. Furthermore, these policies will still be necessary in a phased vaccination program. Therefore, health surveillance activities should be maintained along with vaccination planning in scheduled groups until a large vaccinated coverage is reached. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; https://doi.org/10.1101/2021.01.27.21250651 doi: medRxiv preprint The ODE system which resumes this model is: The model enables the application of intervention measures with the social distancing of specific age 55 groups. Social distancing affects people in reducing the probability of encounters between infected 56 and susceptible individuals. Thus, we simulate this condition by reducing the infection rates β, β A , 57 β I and β Im for the specific age groups. Due to imperfect application of social distancing intervention, 58 each intervention is controlled by a success rate. 59 The fact that the model is stratified by age groups opens a new range of different scenarios, e.g., when applying the social distancing intervention to younger age groups, we can simulate a closed 61 schools condition. The reduction is applied to the R 0 , from which the infection rates are calculated, 62 value multiplying it by the reduction factor κ with a pre-defined value. The social distancing applied 63 to the 0-20 years old age groups is labeled SD-Y, when applied to the age groups higher than 60 years 64 old is labeled SD-E, and when we apply the reduction to all age groups, we label this condition as SD-A. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint Another intervention possibility is when tests are applied to the individuals, and a quarantine 71 is applied where symptomatic cases are isolated with a probability σ and asymptomatic with a 72 probability σ A , this condition is labeled as TQ-C. In this scenario, we modify the susceptible flow 73 equation to If we only isolate the severe cases (scenario TQ), we change the susceptible individuals flow 75 equation to The scenario where we only isolate the severe cases is termed TS, and we modify the susceptible 77 flow equation to The exposed, vaccinated, and falsely immunized are changed just like the susceptible flow, 79 depending on the scenario. The Table 1 summarizes the parameters used in the model with their respective values and 81 references. The parameter β is calculated from the previous definition of R 0 value, the asymptomatic value 83 f A , the probability of developing symptoms ρ S , and the incubation time τ inc with The infection rate regarding asymptomatic individuals is obtained by the product of β with f A , 85 while the infection rate regarding asymptomatic individuals is obtained from the product of β with is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; https://doi.org/10.1101/2021.01.27.21250651 doi: medRxiv preprint Throughout the pandemic, the scenario was altered several times due to governmental decisions 98 of applying the interventions or making them more flexible and the incomplete adherence of the 99 population. In this section, we evaluate how the model behaves when we use the same quarantine 100 severity as applied by the government for each period while comparing the results to real-time data. Our approach is based on the Rio de Janeiro municipality and state real pandemic decrees, with is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; https://doi.org/10.1101/2021.01.27.21250651 doi: medRxiv preprint (day 1 to day 74). Starting from 16 March 2020 until 27 March 2020 (day 75 to day 86), we consider 104 that this is the beginning of the pandemic, where the government started to apply some intervention 105 measures. However, the population was still not impacted by the severity of the pandemic. Therefore 106 we considered the social distancing of young age and elderly groups, together with the quarantine of 107 only severe cases. From 28 March 2020 to 4 April 2020 (day 87 to day 107), social distancing becomes more 109 widespread, and therefore we consider a social distancing of all age groups. From 5 April 2020 to 110 14 May 2020, the interventions become more restrictive, and now the isolation of cases extends to 111 symptomatic cases when confirmed by testing. A higher isolation rate is considered between the dates To better fit the model to the real notification data, we estimated R 0 = 2.6, the reduction factor 119 of the social distancing to be 0.72, the success in isolating symptomatic cases to be 0.60, while 0.20 for 120 the asymptomatic cases. Also, we considered that the first cases were imported on 11 February 2020.. Reporting rate of severe cases (SARI) are 96% of the real cases, accounting for small under-reporting, 122 whereas under-reporting of notified ARI disease cases are 20% of the actual number of ARI cases. The number of SARI cases notified in the city of Rio de Janeiro, daily aggregated, is evaluated 124 from January to the end of October of 2020. Regarding the ARI notified cases, the data is evaluated 125 from January to the end of September of 2020. This data range is considered an acceptable range to 126 avoid the effect of dramatic sub notification due to notification delay. Vaccination schedules are still being studied for SARS-CoV-2, with different strategies being applied 129 due to diverse factors [10] . However, we expect that this schedule might closely follow other 130 respiratory syndromes' vaccination, like influenza. In this work, we will consider an effective, tight, 131 and compromised vaccination program to assess if this would be enough to halt the pandemic 132 effectively. Therefore, our vaccination schedule is comprised of 4 phases, each lasting for 15 days. In the first phase, individuals older than 60 years old are vaccinated at a rate of 1.0%. Critical is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. Table 1 , with the exception of R 0 , which is 3.5. As shown in Fig.2 , there is a marked difference in the effectiveness of each intervention alone. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; https://doi.org/10.1101/2021.01.27.21250651 doi: medRxiv preprint minimal delaying effect at the peak. A combination of mitigation policies makes significant impact in 149 the peak of number of cases. As our model is stratified by age groups, we also observe how the different interventions change 151 the number of deaths and hospitalizations by age, as shown by Fig.3 . The quarantine of all cases, the 152 social distancing of all individuals, and the combination of this intervention with the quarantine of 153 symptomatic cases are the three most effective interventions, as also seen by Fig.2 . In all cases, despite 154 isolating or distancing different age groups, the pattern of hospitalizations and deaths regarding age 155 groups is very similar. The major difference is observed in delaying the pandemic peak and the 156 pandemic's length, broadening its profile through time, but not through age groups. Hospitalizations 157 are centered around older groups, mainly individuals around 60 years old and older, in all interventions. Concerning hospitalizations, there is a more even distribution among age groups. However, it is 159 essential to note that hospitalizations of young age individuals (younger than 30 years old) are 160 considerably pronounced. 161 Also, in Figure 3 , despite profile similarity across age groups, some age groups are more affected 162 since the beginning of the pandemic and at the end. There is a distortion of the profile's rectangular 163 shape observed in almost all scenarios, in favor of a more oval-oriented shape, which is more pronounced 164 in the SD-A and TQ, only TQ, and only TQ-C scenarios. 165 Regarding the case study of Rio de Janeiro municipality, as shown by Fig. 4 , the model presents Even though a second peak is not yet reached in Rio de Janeiro as of now by the official notified 176 data, it is seen in Fig. 4 that ARI notified cases are on the rise. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; Model results for new daily symptomatic cases and ARI notified cases in Rio de Janeiro (B). Notified cases of SARI and ARI in Rio de Janeiro are represented by black lines, other colors represent the different simulated scenarios: social distancing is abandoned (orange), the quarantine strengthening together with the social distancing of all groups and isolation of both symptomatic and asymptomatic individuals (pink), and current social distancing with symptomatic isolation scenario is maintained (green). Red lines represents the median values in each scenario. . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. The main objective of NPI interventions is to mitigate the effect of the pandemic for a proper health 189 care attention to mild and severe cases. As shown by Fig.2 independently from the nature of the 190 intervention (social distancing or isolation of cases), as expected and seen in many studies [1, [11] [12] [13] , 191 delaying the epidemic peak is a consequence of the reduction in transmission intensity. highlights the importance of an enforced isolation measure, as the asymptomatic cases also impact in and economic distress of a population during interventions [21, 22] . It is imperative to also observe This is a crucial moment to study and show that we must yet consider the application of strict 255 interventions of social distancing, isolation, and vaccination as the risk of SARS-CoV-2 transmission 256 is present in multiple countries. The modelling in this work shows that effective control of the 257 COVID-19 pandemic requires a combination of these efforts. All SARI and ARI notification data are publicly available at OpenDataSUS database, maintained by the Ministry of Health, located at https://opendatasus.saude.gov.br/. 17 . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 31, 2021. ; https://doi.org/10.1101/2021.01.27.21250651 doi: medRxiv preprint Evaluating the effectiveness of social distancing interventions to delay or flatten the epidemic curve of coronavirus disease. 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