ArticleInfectious Disease Modelling2026
Optimal prevention and control strategy of infectious disease: Cost-effectiveness analysis based on a modified dynamic model with economic loss.
Article in Infectious Disease Modelling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The large-scale outbreaks of novel infectious diseases threaten public health, while strict intervention measures might slow down the economic activity. The effective prevention and control measures should balance cost and benefit. This study aims to explore the optimal intervention strategy for the infectious diseases by proposing a dynamic model with economic cost based on the modified SEIR model. Seven compartments were expanded as QSEAIRD model according to China's real practice in COVID-19. The parameters were estimated by minimizing the prediction error, and the GDP loss coefficients were introduced to quantify the economic costs of different measures. Thereafter, we formulated a corresponding algorithm to solve for the optimal prevention policies, which could control the epidemic within a specified time with minimized economic loss. Using Shanghai as a case study, we simulated the epidemic trends from March 2022 under different policy scenarios. We found that the government interventions effectively shortened the peak time by 60 % and significantly reduced its magnitude by 90 %. Without these measures, we predicted that Shanghai would reach the peaks of the first and second waves of infections at the end of 2022 and in June 2023, respectively, with the number of infections during the second peak being about 1/7 of that during the first. These results demonstrate that the government's prevention and control measures were effective in containing the epidemic. If relatively loose measures were adopted, the epidemic would not be controlled within one month, which would prolong the implementation of the prevention measures and increase economic loss. By conducting a cost-effectiveness analysis, the proposed model and algorithm can be flexibly applied to optimize the design of infectious disease prevention and control schemes under different scenarios, systematically enhancing the capacity to respond to the novel infectious diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.