Journal Home Online First Current Issue Archive For Authors Journal Information 中文版

Engineering >> 2021, Volume 7, Issue 7 doi: 10.1016/j.eng.2021.03.020

A Scenario-Based Evaluation of COVID-19-Related Essential Clinical Resource Demands in China

a School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
b Division of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China
c Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of Guilin Medical University, Guilin 541001, China

# These authors contributed equally to this work.

Received: 2021-01-17 Revised: 2021-02-15 Accepted: 2021-03-25 Available online: 2021-05-21

Next Previous

Abstract

The coronavirus disease 2019 (COVID-19) pandemic is a global crisis, and medical systems in many countries are overwhelmed with supply shortages and increasing demands to treat patients due to the surge in cases and severe illnesses. This study aimed to assess COVID-19-related essential clinical resource demands in China, based on different scenarios involving COVID-19 outbreaks and interventions. We used a susceptible–exposed–infectious–hospitalized/isolated–removed (SEIHR) transmission dynamics model to estimate the number of COVID-19 infections and hospitalizations with corresponding essential healthcare resources needed. We found that, under strict non-pharmaceutical interventions (NPIs) or mass vaccination of the population, China would be able to contain community transmission and local outbreaks rapidly. However, under scenarios involving a low intensity of implemented NPIs and a small proportion of the population vaccinated, the use of a peacetime–wartime transition model would be needed for medical source stockpiles and preparations to ensure a normal functioning healthcare system. The implementation of COVID-19 vaccines and NPIs in different periods can influence the transmission of COVID-19 and subsequently affect the demand for clinical diagnosis and treatment. An increased proportion of asymptomatic infections in simulations will not reduce the demand for medical resources; however, attention must be paid to the increasing difficulty in containing COVID-19 transmission due to asymptomatic cases. This study provides evidence for emergency preparations and the adjustment of prevention and control strategies during the COVID-19 pandemic. It also provides guidance for essential healthcare investment and resource allocation.

Figures

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

References

[ 1 ] Timeline: WHO’s COVID-19 response [Internet]. Geneva: World Health Organization; [cited 2020 Dec 20]. Available from: https://www.who.int/ emergencies/diseases/novel-coronavirus-2019/interactive-timeline. link1

[ 2 ] WHO coronavirus (COVID-19) dashboard [Internet]. Geneva: World Health Organization; [cited 2020 Dec 20]. Available from: https://covid19.who.int/. link1

[ 3 ] Lai S, Ruktanonchai NW, Zhou L, Prosper O, Luo W, Floyd JR, et al. Effect of nonpharmaceutical interventions to contain COVID-19 in China. Nature 2020;585 (7825):410–3. link1

[ 4 ] Pan A, Liu L, Wang C, Guo H, Hao X, Wang Q, et al. Association of public health interventions with the epidemiology of the COVID-19 outbreak. JAMA 2020;323(19):1915–23. link1

[ 5 ] Li Z, Chen Q, Feng L, Rodewald L, Xia Y, Yu H, et al. Active case finding with case management: the key to tackling the COVID-19 pandemic. Lancet 2020;396 (10243):63–70. link1

[ 6 ] Fallucchi F, Faravelli M, Quercia S. Fair allocation of scarce medical resources in the time of COVID-19: what do people think? J Med Ethics 2021;47(1):3–6. link1

[ 7 ] Wuhan Statistical Bureau. Wuhan statistical yearbook 2018 [Internet]. Wuhan: Wuhan Statistical Bureau; 2018 [cited 2020 Dec 20]. Available from: http://tjj. wuhan.gov.cn/tjfw/tjnj/202004/P020200426461240969401.pdf. Chinese. link1

[ 8 ] Hospital beds (per 1,000 people) [Internet]. Washington, DC: The World Bank; [cited 2020 Dec 20]. Available from: https://data.worldbank.org/indicator/SH. MED.BEDS.ZS?end=2015&name_desc=false&start=1960&view=chart. link1

[ 9 ] Italy [Internet]. Washington, DC: The World Bank; 2020 [cited 2020 Dec 20]. Available from: https://data.worldbank.org/country/italy. link1

[10] Coronavirus (COVID-19) action plan [Internet]. London: Department of Health and Social Care; 2020 Mar 3 [cited 2020 Dec 20]. Available from: https:// www.gov.uk/government/publications/coronavirus-action-plan. link1

[11] Anthony C, Thomas TJ, Berg BM, Burke RV, Upperman JS. Factors associated with preparedness of the US healthcare system to respond to a pediatric surge during an infectious disease pandemic: is our nation prepared? Am J Disaster Med 2017;12(4):203–26. link1

[12] Legido-Quigley H, Mateos-García JT, Campos VR, Gea-Sánchez M, Muntaner C, McKee M. The resilience of the Spanish health system against the COVID-19 pandemic. Lancet Public Health 2020;5(5):e251–2. link1

[13] Chen S, Chen Q, Yang W, Xue L, Liu Y, Yang J, et al. Buying time for an effective epidemic response: the impact of a public holiday for outbreak control on COVID-19 epidemic spread. Engineering 2020;6(10):1108–14. link1

[14] Chen S, Zhang Z, Yang J, Wang J, Zhai X, Bärnighausen T, et al. Fangcang shelter hospitals: a novel concept for responding to public health emergencies. Lancet 2020;395(10232):1305–14. link1

[15] COVID-19: why is medical system in metropolises so vulnerable? [Internet]. Beijing: China.org.cn; 2020 Apr 21 [cited 2020 Dec 20]. Available from: http:// www.china.org.cn/opinion/2020-04/21/content_75957964.htm. link1

[16] Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? Lancet 2020;395 (10231):1225–8. link1

[17] Liu J, Zhang L, Yan Y, Zhou Y, Yin P, Qi J, et al. Excess mortality in Wuhan city and other parts of China during the three months of the COVID-19: findings from nationwide mortality registries. BMJ 2021;372:n415.

[18] Willan J, King AJ, Jeffery K, Bienz N. Challenges for NHS hospitals during COVID-19 epidemic. BMJ 2020;368:m1117. link1

[19] Fineberg HV. Pandemic preparedness and response—lessons from the H1N1 influenza of 2009. N Engl J Med 2014;370(14):1335–42. link1

[20] Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak. JAMA 2020;323(13):1239–42. link1

[21] Spellberg B, Haddix M, Lee R, Butler-Wu S, Holtom P, Yee H, et al. Community prevalence of SARS-CoV-2 among patients with influenza like illnesses presenting to a Los Angeles medical center. JAMA 2020;323(19):1966–7. link1

[22] www.who.int [Internet]. Geneva: WHO; 2020 [cited 2020 Dec 20]. Available from: https://www.who.int/publications/m/item/covid-19-essential-suppliesforecasting-tool. link1

[23] Walker PGT, Whittaker C, Watson OJ, Baguelin M, Winskill P, Hamlet A, et al. The impact of COVID-19 and strategies for mitigation and suppression in lowand middle-income countries. Science 2020;369(6502):413–22. link1

[24] Rainisch G, Undurraga EA, Chowell G. A dynamic modeling tool for estimating healthcare demand from the COVID-19 epidemic and evaluating populationwide interventions. Int J Infect Dis 2020;96:376–83. link1

[25] Eubank S, Eckstrand I, Lewis B, Venkatramanan S, Marathe M, Barrett CL. Commentary on Ferguson, et al., ‘‘Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand”. Bull Math Biol 2020;82(4):52. link1

[26] [Notice on the issuance of the COVID-19 control programme (seventh edition)] [Internet]. Beijing: National Health Commission of the People’s Republic of China; 2020 Sep 15 [cited 2020 Dec 20]. Available from: http://www.nhc.gov. cn/jkj/s3577/202009/318683cbfaee4191aee29cd774b19d8d.shtml. Chinese. link1

[27] Polack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and efficacy of the BNT162b2 mRNA COVID-19 vaccine. N Engl J Med 2020;383 (27):2603–15. link1

[28] [China statistical yearbook 2020] [Internet]. Beijing: National Bureau of Statistics of the People’s Republic of China; c2020 [cited 2020 Dec 20]. Available from: http://www.stats.gov.cn/tjsj/ndsj/2020/indexch.htm. Chinese. link1

[29] [2019 Wuhan statistical bulletin on national economic and social development] [Internet]. Wuhan: Wuhan Bureau of Statistics; 2020 Mar 29 [cited 2020 Dec 20]. Available from: http://tjj.wuhan.gov.cn/tjfw/tjgb/202004/ t20200429_1191417.shtml. Chinese. link1

[30] Lei Q, Li Y, Hou HY, Wang F, Ouyang ZQ, Zhang Y, et al. Antibody dynamics to SARS-CoV-2 in asymptomatic COVID-19 infections. Allergy 2021;76(2):551–61. link1

[31] McAloon C, Collins Á, Hunt K, Barber A, Byrne AW, Butler F, et al. Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research. BMJ Open 2020;10(8):e039652. link1

[32] Wiersinga WJ, Rhodes A, Cheng AC, Peacock SJ, Prescott HC. Pathophysiology, transmission, diagnosis, and treatment of coronavirus disease 2019 (COVID19): a review. JAMA 2020;324(8):782–93. link1

[33] Walsh KA, Jordan K, Clyne B, Rohde D, Drummond L, Byrne P, et al. SARS-CoV-2 detection, viral load and infectivity over the course of an infection. J Infect 2020;81(3):357–71. link1

[34] Li LQ, Huang T, Wang YQ, Wang ZP, Liang Y, Huang TB, et al. COVID-19 patients’ clinical characteristics, discharge rate, and fatality rate of metaanalysis. J Med Virol 2020;92(6):577–83. link1

[35] Yang J, Chen X, Deng X, Chen Z, Gong H, Yan H, et al. Disease burden and clinical severity of the first pandemic wave of COVID-19 in Wuhan, China. Nat Commun 2020;11(1):5411. link1

[36] Zhang T, Wu HT, Wang LH, Yang WZ. Scenario-based study of medical resource requirement rapid assessment under the COVID-19 pandemic. Chin J Epidemiol 2020;41:E059. link1

[37] [Shenzhen statistical yearbook 2020] [Internet]. Shenzhen: Shenzhen Statistics Bureau; c2020 [cited 2020 Dec 20]. Available from: http://tjj.sz.gov.cn/zwgk/ zfxxgkml/tjsj/tjnj/content/post_8386382.html. Chinese. link1

[38] [Shijiazhuang statistical yearbook 2018] [Internet]. Shijiazhuang: Shijiazhuang Bureau of Statistics; 2019 Sep 10 [cited 2020 Dec 20]. Available from: http:// tjj.sjz.gov.cn/col/1584345186126/2019/09/10/1577770888846.html. Chinese. link1

[39] Tian H, Liu Y, Li Y, Wu CH, Chen B, Kraemer MUG, et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science 2020;368(6491):638–42. link1

[40] Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382(18):1708–20. link1

[41] Armaignac DL, Saxena A, Rubens M, Valle CA, Williams LS, Veledar E, et al. Impact of telemedicine on mortality, length of stay, and cost among patients in progressive care units. Crit Care Med 2018;46(5):728–35. link1

[42] Qiu J. Covert coronavirus infections could be seeding new outbreaks [Internet]. Heidelberg: Springer Nature Limited; 2020 [cited 2020 Dec 20]. Available from: https://www.nature.com/articles/d41586-020-00822-x. link1

[43] Wei Y, Wei L, Jiang Y, Shen S, Zhao Y, Hao Y, et al. Implementation of clinical diagnostic criteria and universal symptom survey contributed to lower magnitude and faster resolution of the COVID-19 epidemic in Wuhan. Engineering 2020;6(10):1141–6. link1

Related Research