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Microsimulation based quantitative analysis of COVID-19 management strategies.

ABSTRACT: Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation framework PanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus variant in a city-sized societal environment using a unified framework fitted to realistic data. We show that vaccination strategies prioritising occupational risk groups minimise the number of infections but allow higher mortality while prioritising vulnerable groups minimises mortality but implies an increased infection rate. We also found that intensive vaccination along with non-pharmaceutical interventions can substantially suppress the spread of the virus, while low levels of vaccination, premature reopening may easily revert the epidemic to an uncontrolled state. Our analysis highlights that while vaccination protects the elderly from COVID-19, a large percentage of children will contract the virus, and we also show the benefits and limitations of various quarantine and testing scenarios. The uniquely detailed spatio-temporal resolution of PanSim allows the design and testing of complex, specifically targeted interventions with a large number of agents under dynamically changing conditions.

SUBMITTER: Reguly IZ

PROVIDER: S-EPMC8759654 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Microsimulation based quantitative analysis of COVID-19 management strategies.

Reguly István Z IZ Csercsik Dávid D Juhász János J Tornai Kálmán K Bujtár Zsófia Z Horváth Gergely G Keömley-Horváth Bence B Kós Tamás T Cserey György G Iván Kristóf K Pongor Sándor S Szederkényi Gábor G Röst Gergely G Csikász-Nagy Attila A

PLoS computational biology 20220104 1

Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation framework PanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus ...[more]

PMID: 34982766

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Project description:Purpose: The goals of this study are to compare NGS-derived transcriptome profiling (RNA-seq) of COVID-19 kidney to normal controls Methods/Results: Kidney mRNA profile of human COVID-19 tissue was generated by deep sequencing using Illumina Novaseq6000 Paired-end 150. After filtering reads mapped to contamination database, the reads that were uniquely aligned to the exon and splicing-junction segments with a maximal 2 mismatches for each transcript were then counted as expression level for corresponding transcript. Next, RNA-seq reads count data were downloaded from public resource GTEx project (https://www.gtexportal.org/home/datasets) and 12 normal kidney tissue samples were extracted as controls. The differential analysis by fold change difference was carried out to identify dysregulated genes at 1.5 fold change. The differential expressed genes were then subjected to Gene Ontology function and Pathway (KEGG, Ingenuity IPA, BIOCARTA, NABA, Panther, PID, REACTOME, Wiki-pathway) enrichment analysis by Fisher-exact test. Conclusions: RNA sequencing data revealed that biological processes from upregulated genes were enriched for cell cycle, chromosome segregation, response to wounding, humoral immune response, and blood coagulation, suggesting that cell injury/regeneration, inflammatory response, and endothelial injury were the major disease processes involved. The biological processes from downregulated genes were enriched for ion transport, metabolic processes, and oxidation, likely secondary to severe tubular cell injury. Pathway analysis from both up- and downregulated genes showed enrichment of transmembrane transport, oxidation, and blood coagulation consistent with the GO terms analysis. Upregulated genes were enriched only for the FOXM1 pathway, which was recently reported to promote tubular cell proliferation during injury repair. Additionally, genes related to the renin-angiotensin system were downregulated, but ACE2 expression did not differ from normal controls.

Project description:Healthcare resource constraints in low and middle-income countries necessitate selection of cost-effective public health interventions to address COVID-19. We developed a dynamic COVID-19 microsimulation model to evaluate clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal, South Africa. Interventions assessed were Healthcare Testing (HT), where diagnostic testing is performed only for those presenting to healthcare centres; Contact Tracing (CT) in households of cases; Isolation Centres (IC), for cases not requiring hospitalisation; community health worker-led Mass Symptom Screening and molecular testing for symptomatic individuals (MS); and Quarantine Centres (QC), for household contacts who test negative. Given uncertainties about epidemic dynamics in South Africa, we evaluated two main epidemic scenarios over 360 days, with effective reproduction numbers (Re) of 1·5 and 1·2. We compared HT, HT+CT, HT+CT+IC, HT+CT+IC+MS, HT+CT+IC+QC, and HT+CT+IC+MS+QC, considering strategies with incremental cost-effectiveness ratio (ICER) <US$3,250/year-of-life saved (YLS) cost-effective. In sensitivity analyses, we varied Re, molecular testing sensitivity, and efficacies and costs of interventions. With Re 1·5, HT resulted in the most COVID-19 deaths over 360 days. Compared with HT, HT+CT+IC+MS+QC reduced mortality by 94%, increased costs by 33%, and was cost-effective (ICER $340/YLS). In settings where quarantine centres cannot be implemented, HT+CT+IC+MS was cost-effective compared with HT (ICER $590/YLS). With Re 1·2, HT+CT+IC+QC was the least costly strategy, and no other strategy was cost-effective. HT+CT+IC+MS+QC was cost-effective in many sensitivity analyses; notable exceptions were when Re was 2·6 and when efficacies of ICs and QCs for transmission reduction were reduced. In South Africa, strategies involving household contact tracing, isolation, mass symptom screening, and quarantining household contacts who test negative would substantially reduce COVID-19 mortality and be cost-effective. The optimal combination of interventions depends on epidemic growth characteristics and practical implementation considerations.

Project description:BackgroundHealth-care resource constraints in low-income and middle-income countries necessitate the identification of cost-effective public health interventions to address COVID-19. We aimed to develop a dynamic COVID-19 microsimulation model to assess clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal province, South Africa.MethodsWe compared different combinations of five public health interventions: health-care testing alone, where diagnostic testing is done only for individuals presenting to health-care centres; contact tracing in households of cases; isolation centres, for cases not requiring hospital admission; mass symptom screening and molecular testing for symptomatic individuals by community health-care workers; and quarantine centres, for household contacts who test negative. We calibrated infection transmission rates to match effective reproduction number (Re) estimates reported in South Africa. We assessed two main epidemic scenarios for a period of 360 days, with an Re of 1·5 and 1·2. Strategies with incremental cost-effectiveness ratio (ICER) of less than US$3250 per year of life saved were considered cost-effective. We also did sensitivity analyses by varying key parameters (Re values, molecular testing sensitivity, and efficacies and costs of interventions) to determine the effect on clinical and cost projections.FindingsWhen Re was 1·5, health-care testing alone resulted in the highest number of COVID-19 deaths during the 360-day period. Compared with health-care testing alone, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres reduced mortality by 94%, increased health-care costs by 33%, and was cost-effective (ICER $340 per year of life saved). In settings where quarantine centres were not feasible, a combination of health-care testing, contact tracing, use of isolation centres, and mass symptom screening was cost-effective compared with health-care testing alone (ICER $590 per year of life saved). When Re was 1·2, health-care testing, contact tracing, use of isolation centres, and use of quarantine centres was the least costly strategy, and no other strategies were cost-effective. In sensitivity analyses, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres was generally cost-effective, with the exception of scenarios in which Re was 2·6 and when efficacies of isolation centres and quarantine centres for transmission reduction were reduced.InterpretationIn South Africa, strategies involving household contact tracing, isolation, mass symptom screening, and quarantining household contacts who test negative would substantially reduce COVID-19 mortality and would be cost-effective. The optimal combination of interventions depends on epidemic growth characteristics and practical implementation considerations.FundingUS National Institutes of Health, Royal Society, Wellcome Trust.

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Microsimulation based quantitative analysis of COVID-19 management strategies.

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Microsimulation based quantitative analysis of COVID-19 management strategies.

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