Michael Balzer, Kainat Khowaja, Christiane Fuchs
arXiv 30 Mar 2026 · Statistics — Computation
arXiv:2603.28930 · PDF · DOI · OpenAlex · Extracted main text
Surveillance of diseases in a pandemic is an important part of public health policy. Diagnostic testing at the individual level is often infeasible due to resource constraints. To circumvent these constraints, group testing can be applied. The economic cost evaluation from the payer's perspective typically focuses only on deterministic costs which overlooks the substantial economic impact of productivity losses resulting from quarantine and workplace disruptions. The objective of this article is to develop a mathematical model for a retrospective economic evaluation of group testing that incorporates both deterministic costs and income-based economic loss. Group testing algorithms are revisited and simulated at optimized pool sizes to determine the required number of tests. Income data from the German Socio-Economic Panel are integrated into a mathematical model to capture the economic loss. Afterward, hybrid Monte Carlo experiments are conducted by evaluating the economic cost in the Coronavirus disease 2019 pandemic in Germany. Monte Carlo experiments show that the optimal choice of group testing algorithms changes substantially when income-based economic losses are included. Evaluations considering only deterministic costs systematically underestimate the total economic cost. Algorithms with a longer quarantine duration are less attractive than shorter quarantine duration if income-based economic loss is accounted for. The findings show that current evaluations underestimate the true economic cost. Group testing algorithms with shorter duration and fewer stages are preferred, even when they require a larger number of tests. These results underscore the importance of incorporating income-based economic loss into a mathematical model.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Aldridge, Matthew and Ellis, David (2022) Pooled Testing and Its Applications in the COVID-19 Pandemic | 1.000 | 6 | 3 | 100% |
| 2 | Mutesa, L. and Ndishimye, P. and Butera, Y. and Souopgui, J. and Uwi… (2021) A pooled testing strategy for identifying SARS-CoV-2 at low prevalence | 1.000 | 5 | 3 | 100% |
| 3 | Brandt, F. and Simone, G. and Loth, J. and Schilling, D (2024) COVID-19-associated costs and mortality in Germany: an incidence-based analysis from a payer's perspective | 0.843 | 3 | 3 | 100% |
| 4 | Robert Dorfman (1943) The Detection of Defective Members of Large Populations | 0.811 | 4 | 2 | 100% |
| 5 | R. Diel and A. Nienhaus (2022) Point-of-care COVID-19 antigen testing in German emergency rooms – a cost-benefit analysis | 0.644 | 2 | 2 | 100% |
| 6 | J.N. Eberhardt and N.P. Breuckmann and C.S. Eberhardt (2020) Multi-Stage Group Testing Improves Efficiency of Large-Scale COVID-19 Screening | 0.644 | 2 | 2 | 100% |
| 7 | Hwang, Frank K (1972) A method for detecting all defective members in a population by group testing | 0.644 | 2 | 2 | 100% |
| 8 | Bundesministerium für Justiz (2021) Gesetz zur Verhütung und Bekämpfung von Infektionskrankheiten beim Menschen (Infektionsschutzgesetz - IfSG) | 0.644 | 2 | 2 | 100% |
| 9 | Nguyen, H. T. and Denkinger, C. M. and Brenner, S. and Koeppel, L. a… (2023) Cost and cost-effectiveness of four different SARS-CoV-2 active surveillance strategies: evidence from a randomised control tria… | 0.644 | 2 | 2 | 100% |
| 10 | Pighi, Laura and Henry, Brandon M. and Mattiuzzi, Camilla and De Nit… (2023) Cost-effectiveness analysis of different COVID-19 screening strategies based on rapid or laboratory-based SARS-CoV-2 antigen tes… | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 35 scored citations.