Modeling the optimization of COVID-19 pooled testing: How many samples can be included in a single test?

Liu, Lu

doi:10.1016/j.imu.2022.101037

Cited by 4 publications

(2 citation statements)

References 44 publications

(48 reference statements)

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“…Second, the data available mainly focuses on particular age groups, which could impact the results of our study. Therefore, we need to use sufficient data as proposed by [ 85 ] for further evaluation. Further research is warranted to validate its diagnostic value in a population consists of microcytic anemia and various types of anemia.…”

Section: Discussionmentioning

confidence: 99%

Multi-criteria decision making to validate performance of RBC-based formulae to screen $$\beta$$-thalassemia trait in heterogeneous haemoglobinopathies

Jain,

Sharma,

Saleh

et al. 2024

BMC Med Inform Decis Mak

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Background India has the most significant number of children with thalassemia major worldwide, and about 10,000-15,000 children with the disease are born yearly. Scaling up e-health initiatives in rural areas using a cost-effective digital tool to provide healthcare access for all sections of people remains a challenge for government or semi-governmental institutions and agencies. Methods We compared the performance of a recently developed formula SCS$$_{BTT}$$ BTT and its web application SUSOKA with 42 discrimination formulae presently available in the literature. 6,388 samples were collected from the Postgraduate Institute of Medical Education and Research, Chandigarh, in North-Western India. Performances of the formulae were evaluated by eight different measures: sensitivity, specificity, Youden’s Index, AUC-ROC, accuracy, positive predictive value, negative predictive value, and false omission rate. Three multi-criteria decision-making (MCDM) methods, TOPSIS, COPRAS, and SECA, were implemented to rank formulae by ensuring a trade-off among the eight measures. Results MCDM methods revealed that the Shine & Lal and SCS$$_{BTT}$$ BTT were the best-performing formulae. Further, a modification of the SCS$$_{BTT}$$ BTT formula was proposed, and validation was conducted with a data set containing 939 samples collected from Nil Ratan Sircar (NRS) Medical College and Hospital, Kolkata, in Eastern India. Our two-step approach emphasized the necessity of a molecular diagnosis for a lower number of the population. SCS$$_{BTT}$$ BTT along with the condition MCV$$\le$$ ≤ 80 fl was recommended for a higher heterogeneous population set. It was found that SCS$$_{BTT}$$ BTT can classify all BTT samples with 100% sensitivity when MCV$$\le$$ ≤ 80 fl. Conclusions We addressed the issue of how to integrate the higher-ranked formulae in mass screening to ensure higher performance through the MCDM approach. In real-life practice, it is sufficient for a screening algorithm to flag a particular sample as requiring or not requiring further specific confirmatory testing. Implementing discriminate functions in routine screening programs allows early identification; consequently, the cost will decrease, and the turnaround time in everyday workflows will also increase. Our proposed two-step procedure expedites such a process. It is concluded that for mass screening of BTT in a heterogeneous set of data, SCS$$_{BTT}$$ BTT and its web application SUSOKA can provide 100% sensitivity when MCV$$\le$$ ≤ 80 fl.

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Section: Discussionmentioning

confidence: 99%

Multi-criteria decision making to validate performance of RBC-based formulae to screen $$\beta$$-thalassemia trait in heterogeneous haemoglobinopathies

Jain,

Sharma,

Saleh

et al. 2024

BMC Med Inform Decis Mak

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“…However, available data on daily RT-PCR testing were on tests done on an individual basis. Liu [ 81 ] describes an optimization technique commonly employed in economics and management wherein: a theoretical model linking the local population tested for COVID-19 in a specific region, the quantity of biological samples that can be incorporated into a single test, along with the associated resource cost and time functions is constructed; numerical simulation outcomes are leveraged to establish both the resource cost and time functions and; a minimizable loss function is devised, and the optimal quantity of included samples is computed. Unfortunately, due to the ecological design of our study, it may be problematic to incorporate such optimizing techniques as local instead of country-level COVID-19 infection probabilities need to be introduced.…”

Section: Discussionmentioning

confidence: 99%

Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic

Van Haute,

Agagon,

Gumapac

et al. 2023

PLOS Glob Public Health

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A positive correlation has been demonstrated between gross domestic product (GDP) per capita and COVID-19 tests per 1000 people. Although frequently used as an indicator of economic performance, GDP per capita does not directly reflect income distribution inequalities and imposed health costs. In this longitudinal ecological study, we aimed to determine if, besides GDP per capita, indicators relating to governance, public health measures enforcement, and health and research investment explain differences in RT-PCR testing rates among countries in Southeast Asia (SEA) during the first six months of the COVID-19 pandemic. Using open-access COVID-19 panel data, we estimated the effect of various indicators (GDP per capita, health expenditure per capita, number of researchers per one million population, corruption perceptions index, stringency index, regional authority index) on daily COVID-19 testing by performing fixed-effects negative binomial regression. After accounting for all indicators, the number of daily confirmed COVID-19 cases, and population density, the model provided a 2019 GDP per capita coefficient of 0.0046330 (95% CI: 0.0040171, 0.0052488; p <0.001), indicating that a rise in 2019 GDP per capita by 100 international dollars is associated with a 46.33% increase in the number of daily tests performed. Additionally, all indicators were significantly associated with the daily number of RT-PCR testing on multivariable analysis. In conclusion, we identified different country-level indicators significantly associated with differences in COVID-19 testing rates among SEA countries. Due to the study’s ecological design, we caution on applying our results to the individual level given potential for systematic differences between the included countries. Additional investigation is likewise needed to understand how government expenditure on healthcare may have impacted COVID-19 testing capacity during the initial stages of the pandemic.

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A Theory for Covid-19 Testing to Save Both Resources and Time

Lee,

Wang

2023

Int. J. Appl. Comput. Math

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In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the same assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.

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Modeling the optimization of COVID-19 pooled testing: How many samples can be included in a single test?

Cited by 4 publications

References 44 publications

Multi-criteria decision making to validate performance of RBC-based formulae to screen $$\beta$$-thalassemia trait in heterogeneous haemoglobinopathies

Multi-criteria decision making to validate performance of RBC-based formulae to screen $$\beta$$-thalassemia trait in heterogeneous haemoglobinopathies

Determinants of differences in RT-PCR testing rates among Southeast Asian countries during the first six months of the COVID-19 pandemic

A Theory for Covid-19 Testing to Save Both Resources and Time

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