COVID-19: Original Article
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Forecasting the effects of vaccination on the COVID-19 pandemic in Malaysia using SEIRV compartmental models
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Mei Cheng Lim, Sarbhan Singh, Chee Herng Lai, Balvinder Singh Gill, Mohd Kamarulariffin Kamarudin, Ahmed Syahmi Syafiq Md Zamri, Cia Vei Tan, Asrul Anuar Zulkifli, Mohamad Nadzmi Md Nadzri, Nur'ain Mohd Ghazali, Sumarni Mohd Ghazali, Nuur Hafizah Md Iderus, Nur Ar Rabiah Binti Ahmad, Jeyanthi Suppiah, Kok Keng Tee, Tahir Aris, Lonny Chen Rong Qi Ahmad
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Epidemiol Health. 2023;45:e2023093. Published online October 17, 2023
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DOI: https://doi.org/10.4178/epih.e2023093
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Abstract
Summary
PDFSupplementary Material
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Abstract
OBJECTIVES
This study aimed to develop susceptible-exposed-infectious-recovered-vaccinated (SEIRV) models to examine the effects of vaccination on coronavirus disease 2019 (COVID-19) case trends in Malaysia during Phase 3 of the National COVID-19 Immunization Program amidst the Delta outbreak.
METHODS
SEIRV models were developed and validated using COVID-19 case and vaccination data from the Ministry of Health, Malaysia, from June 21, 2021 to July 21, 2021 to generate forecasts of COVID-19 cases from July 22, 2021 to December 31, 2021. Three scenarios were examined to measure the effects of vaccination on COVID-19 case trends. Scenarios 1 and 2 represented the trends taking into account the earliest and latest possible times of achieving full vaccination for 80% of the adult population by October 31, 2021 and December 31, 2021, respectively. Scenario 3 described a scenario without vaccination for comparison.
RESULTS
In scenario 1, forecasted cases peaked on August 28, 2021, which was close to the peak of observed cases on August 26, 2021. The observed peak was 20.27% higher than in scenario 1 and 10.37% lower than in scenario 2. The cumulative observed cases from July 22, 2021 to December 31, 2021 were 13.29% higher than in scenario 1 and 55.19% lower than in scenario 2. The daily COVID-19 case trends closely mirrored the forecast of COVID-19 cases in scenario 1 (best-case scenario).
CONCLUSIONS
Our study demonstrated that COVID-19 vaccination reduced COVID-19 case trends during the Delta outbreak. The compartmental models developed assisted in the management and control of the COVID-19 pandemic in Malaysia.
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Summary
Key Message
The effectiveness of the Coronavirus disease 2019 (COVID-19) vaccination against the highly transmissible Delta variant remained uncertain during the initial phase of the Delta outbreak in Malaysia. The innovative use of compartmental models provided scientific evidence of the potential impact of COVID-19 vaccination in reducing COVID-19 case trends based on local epidemiological data and offered forecasts of COVID-19 case trends based on varying vaccination rates which assisted resource planning and enhanced healthcare system preparedness. This evidence played a crucial role in bolstering public confidence in vaccination efforts and assisted in the control and management of the pandemic.
COVID-19: Original Article
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Effective vaccination strategies to control COVID-19 in Korea: a modeling study
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Youngsuk Ko, Kyong Ran Peck, Yae-Jean Kim, Dong-Hyun Kim, Eunok Jung
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Epidemiol Health. 2023;45:e2023084. Published online September 7, 2023
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DOI: https://doi.org/10.4178/epih.e2023084
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Abstract
Summary
PDFSupplementary Material
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Abstract
OBJECTIVES
In Korea, as immunity levels of the coronavirus disease 2019 (COVID-19) in the population acquired through previous infections and vaccinations have decreased, booster vaccinations have emerged as a necessary measure to control new outbreaks. The objective of this study was to identify the most suitable vaccination strategy for controlling the surge in COVID-19 cases.
METHODS
A mathematical model was developed to concurrently evaluate the immunity levels induced by vaccines and infections. This model was then employed to investigate the potential for future resurgence and the possibility of control through the use of vaccines and antivirals.
RESULTS
As of May 11, 2023, if the current epidemic trend persists without further vaccination efforts, a peak in resurgence is anticipated to occur around mid-October of the same year. Under the most favorable circumstances, the peak number of severely hospitalized patients could be reduced by 43% (n=480) compared to the scenario without vaccine intervention (n=849). Depending on outbreak trends and vaccination strategies, the best timing for vaccination in terms of minimizing this peak varies from May 2023 to August 2023.
CONCLUSIONS
Our findings suggest that if the epidemic persist, the best timing for administering vaccinations would need to be earlier than currently outlined in the Korean plan. It is imperative to continue monitoring outbreak trends, as this is key to determining the best vaccination timing in order to manage potential future surges.
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Summary
Korean summary
본 연구는 자연감염 혹은 백신으로 획득된 면역의 저하를 고려한 수리모델을 사용하여 COVID-19에 대한 백신 접종 전략 분석 결과를 보인다. 시뮬레이션 결과는 추가 백신 접종이 없을 경우 재유행의 정점이 800명을 넘을 것임을 나타내며, 적절한 시기에 백신을 접종하면 최대 재원 위중증환자수를 약 40%까지 줄일 수 있음을 보인다. 본 연구는 확진자 추세의 지속적인 모니터링이 백신 접종의 적정 시기를 결정하고 미래 COVID-19의 재유행을 효과적으로 관리하는 데 필요하다는 점을 강조한다.
Key Message
Our study analyzes strategies for COVID-19 through vaccination, using a mathematical model considering waning immunity from past infections and vaccinations. Results indicate that a resurgence peak would reach more than 800 without further vaccination, and suggest vaccination in proper timing can reduce the peak size of administered severe patients by up to approximately 40%. The study emphasizes the importance of ongoing monitoring of outbreak trends to manage vaccination timing and future COVID-19 surges effectively.
COVID-19: Original Article
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Effectiveness of the movement control measures during the third wave of COVID-19 in Malaysia
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Ahmed Syahmi Syafiq Md Zamri, Sarbhan Singh, Sumarni Mohd Ghazali, Lai Chee Herng, Sarat Chandra Dass, Tahir Aris, Hishamshah Mohd Ibrahim, Balvinder Singh Gill
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Epidemiol Health. 2021;43:e2021073. Published online September 23, 2021
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DOI: https://doi.org/10.4178/epih.e2021073
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7,783
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Abstract
Summary
PDFSupplementary Material
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Abstract
OBJECTIVES
Starting in March 2020, movement control measures were instituted across several phases in Malaysia to break the chain of transmission of coronavirus disease 2019 (COVID-19). In this study, we developed a susceptible-exposed-infected-recovered (SEIR) model to examine the effects of the various phases of movement control measures on disease transmissibility and the trend of cases during the third wave of the COVID-19 pandemic in Malaysia.
METHODS
Three SEIR models were developed using the R programming software ODIN interface based on COVID-19 case data from September 1, 2020, to March 29, 2021. The models were validated and subsequently used to provide forecasts of daily cases from October 14, 2020, to March 29, 2021, based on 3 phases of movement control measures.
RESULTS
We found that the reproduction rate (R-value) of COVID-19 decreased by 59.1% from an initial high of 2.2 during the nationwide Recovery Movement Control Order (RMCO) to 0.9 during the Movement Control Order (MCO) and Conditional MCO (CMCO) phases. In addition, the observed cumulative and daily highest numbers of cases were much lower than the forecasted cumulative and daily highest numbers of cases (by 64.4-98.9% and 68.8-99.8%, respectively).
CONCLUSIONS
The movement control measures progressively reduced the R-value during the COVID-19 pandemic. In addition, more stringent movement control measures such as the MCO and CMCO were effective for further lowering the R-value and case numbers during the third wave of the COVID-19 pandemic in Malaysia due to their higher stringency than the nationwide RMCO.
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Summary
Key Message
• This study developed a susceptible-exposed-infected-recovered (SEIR) model to examine the effects of the various phases of movement control measures on disease transmissibility and the trend of cases during the third wave (September 1, 2020, to March 29, 2021) of the COVID-19 pandemic in Malaysia.
• Finding from this study reports that the reproduction rate (R-value) of COVID-19 and case trends were lower during the implementation of the Movement Control Order (MCO) and Conditional MCO (CMCO) phases
• The MCO and CMCO were effective measures in controlling the COVID-19 outbreak during the third wave in Malaysia due to their higher stringency levels
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Citations
Citations to this article as recorded by
- Assessing the dynamics and impact of COVID-19 vaccination on disease spread: A data-driven approach
Farhad Waseel, George Streftaris, Bhuvendhraa Rudrusamy, Sarat C. Dass
Infectious Disease Modelling.2024; 9(2): 527. CrossRef - Effects of a 7-Day Pornography Abstinence Period on Withdrawal-Related Symptoms in Regular Pornography Users: A Randomized Controlled Study
David P. Fernandez, Daria J. Kuss, Lucy V. Justice, Elaine F. Fernandez, Mark D. Griffiths
Archives of Sexual Behavior.2023; 52(4): 1819. CrossRef - MODIFIED SEIRD MODEL: A NOVEL SYSTEM DYNAMICS APPROACH IN MODELLING THE SPREAD OF COVID-19 IN MALAYSIA DURING THE PRE-VACCINATION PERIOD
Norsyahidah Zulkarnain, Nurul Farahain Mohammad, Ibrahim Shogar
IIUM Engineering Journal.2023; 24(2): 159. CrossRef - Forecasting the effects of vaccination on the COVID-19 pandemic in Malaysia using SEIRV compartmental models
Mei Cheng Lim, Sarbhan Singh, Chee Herng Lai, Balvinder Singh Gill, Mohd Kamarulariffin Kamarudin, Ahmed Syahmi Syafiq Md Zamri, Cia Vei Tan, Asrul Anuar Zulkifli, Mohamad Nadzmi Md Nadzri, Nur'ain Mohd Ghazali, Sumarni Mohd Ghazali, Nuur Hafizah Md I
Epidemiology and Health.2023; 45: e2023093. CrossRef - COVID-19 in Malaysia: Descriptive Epidemiologic Characteristics of the First Wave
Sumarni Mohd Ghazali, Sarbhan Singh, Asrul Anuar Zulkifli, Yoon Ling Cheong, Nuur Hafizah Md Iderus, Ahmed Syahmi Syafiq Md Zamri, Nadhar Ahmad Jaafar, Chee Herng Lai, Wan Noraini Wan Mohamed Noor, Norhayati Rusli, Chee Kheong Chong, Tahir Aris, Hishamsha
International Journal of Environmental Research and Public Health.2022; 19(7): 3828. CrossRef - Impact of immobility and mobility activities on the spread of COVID‐19: Evidence from European countries
Louafi Bouzouina, Karima Kourtit, Peter Nijkamp
Regional Science Policy & Practice.2022; 14(S1): 6. CrossRef - Whole genome sequencing analysis of SARS-CoV-2 from Malaysia: From alpha to Omicron
Choo Yee Yu, Sie Yeng Wong, Nancy Woan Charn Liew, Narcisse Joseph, Zunita Zakaria, Isa Nurulfiza, Hui Jen Soe, Rachna Kairon, Syafinaz Amin-Nordin, Hui Yee Chee
Frontiers in Medicine.2022;[Epub] CrossRef
COVID-19: Original Article
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Risk of COVID-19 transmission in heterogeneous age groups and effective vaccination strategy in Korea: a mathematical modeling study
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Youngsuk Ko, Jacob Lee, Yubin Seo, Eunok Jung
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Epidemiol Health. 2021;43:e2021059. Published online September 8, 2021
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DOI: https://doi.org/10.4178/epih.e2021059
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8,678
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7
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Abstract
Summary
PDFSupplementary Material
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Abstract
OBJECTIVES
This study aims to analyze the possibility and conditions of maintaining an effective reproductive number below 1 using a mathematical model.
METHODS
The total population was divided into five age groups (0-17, 18-29, 30-59, 60-74, and ≥75 years). Maximum likelihood estimation (MLE) was used to estimate the transmission rate of each age group. Mathematical model simulation was conducted until December 31, 2021, by establishing various strategies for vaccination and social distancing without considering variants.
RESULTS
MLE results revealed that the group aged 0-17 years had a lower risk of transmission than other age groups, and the older age group had relatively high risks of infection. If 70% of the population will be vaccinated by the end of 2021, then simulations showed that even if social distancing was eased, the effective reproductive number would remain below 1 near August if it was not at the level of the third re-spreading period. However, if social distancing was eased and it reached the level of the re-spreading period, the effective reproductive number could be below 1 at the end of 2021.
CONCLUSIONS
Considering both stable and worsened situations, simulation results emphasized that sufficient vaccine supply and control of the epidemic by maintaining social distancing to prevent an outbreak at the level of the re-spreading period are necessary to minimize mortality and maintain the effective reproductive number below 1.
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Summary
Korean summary
본 연구에서는 질병관리청에서 제공하는 개별 확진자 데이터에 확률통계적 방법을 적용하여 연령군 간의 감염전파 행렬을 추정하였으며 연령군을 고려한 수리모델에 적용되었다. 본 연구에서 우리는 2020년 10월부터 2021년 5월까지 한국에서의 코로나19 유행상황을 정책 구간에 따라 분석하였으며 이를 토대로 거리두기 완화 수준에 따라 거리두기 완화 상태에서도 지속적으로 유효감염재생산지수가 1보다 작아지는 시점이 달라질 수 있음을 보인다.
Key Message
In this research, we estimated age-group-specified transmission rate matrix by applying maximum likelihood estimation into individual based data which was provided by Korea Disease Control and Prevention Agency. Our model simulation showed the moment, when the effective reproductive number is consistently below 1 even the distancing is eased, is ranged from August to the end of 2021 depending on the intensity of the social distancing during eased phase.
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Citations
Citations to this article as recorded by
- Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review
Oscar Espinosa, Laura Mora, Cristian Sanabria, Antonio Ramos, Duván Rincón, Valeria Bejarano, Jhonathan Rodríguez, Nicolás Barrera, Carlos Álvarez-Moreno, Jorge Cortés, Carlos Saavedra, Adriana Robayo, Oscar H. Franco
Systematic Reviews.2024;[Epub] CrossRef - Risk of Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in Seoul, Korea
Jiwoo Sim, Euncheol Son, Minsu Kwon, Eun Jin Hwang, Young Hwa Lee, Young June Choe
Infection & Chemotherapy.2024;[Epub] CrossRef - Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature
Hyojung Lee, Sol Kim, Minyoung Jeong, Eunseo Choi, Hyeonjeong Ahn, Jeehyun Lee
Yonsei Medical Journal.2023; 64(1): 1. CrossRef - Impact of vaccination and non-pharmacological interventions on COVID-19: a review of simulation modeling studies in Asia
Karan Thakkar, Julia Regazzini Spinardi, Jingyan Yang, Moe H. Kyaw, Egemen Ozbilgili, Carlos Fernando Mendoza, Helen May Lin Oh
Frontiers in Public Health.2023;[Epub] CrossRef - Effective vaccination strategies to control COVID-19 in Korea: a modeling study
Youngsuk Ko, Kyong Ran Peck, Yae-Jean Kim, Dong-Hyun Kim, Eunok Jung
Epidemiology and Health.2023; 45: e2023084. CrossRef - Quantifying the Effects of Non-Pharmaceutical and Pharmaceutical Interventions Against Covid-19 Epidemic in the Republic of Korea: Mathematical Model-Based Approach Considering Age Groups and the Delta Variant
Youngsuk Ko, Victoria May P. Mendoza, Yubin Seo, Jacob Lee, Yeonju Kim, Donghyok Kwon, Eunok Jung, E. Augeraud, M. Banerjee, J.-S. Dhersin, A. d'Onofrio, T. Lipniacki, S. Petrovskii, Chi Tran, A. Veber-Delattre, E. Vergu, V. Volpert
Mathematical Modelling of Natural Phenomena.2022; 17: 39. CrossRef - Dietary Behavior and Diet Quality in the Korean Adult Population by Income Level before and after the COVID-19 Pandemic: Using the Korean National Health and Nutrition Examination Survey (2019-2020)
Hye-Min Na, Bok-Mi Jung
The Korean Journal of Community Living Science.2022; 33(3): 397. CrossRef
Original Articles
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Pain and mortality among older adults in Korea
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Chiil Song, Wankyo Chung
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Epidemiol Health. 2021;43:e2021058. Published online September 7, 2021
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DOI: https://doi.org/10.4178/epih.e2021058
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9,007
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141
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2
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2
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Abstract
Summary
PDFSupplementary Material
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Abstract
OBJECTIVES
With the increasing elderly population with chronic disease, understanding pain and designing appropriate policy interventions to it have become crucial. While pain is a noted mortality risk factor, limited studies exist due to the various causes of pain and the subjectivity of pain expression. This study aimed to examine the relationship between pain and mortality, controlling for other diseases and socio-cultural factors.
METHODS
We analyzed 6,258 individuals aged 45 years or older, the population with the highest prevalence of pain, using the Korean Longitudinal Study of Aging (2006-2016) data and the Cox proportional-hazards model. Further subgroup analyses were conducted by sex and education level to examine differences in the relationship between pain and mortality.
RESULTS
The adjusted hazard ratios of mortality were 1.16 (95% confidence interval [CI], 1.00 to 1.34, model 1) and 1.12 (95% CI, 0.97 to 1.29, model 2) for the individuals in pain depending on the models used, where additional socio-cultural factors were accounted for in model 2. For individuals in severe pain, ratios were significantly higher with 1.23 (95% CI, 1.08 to 1.41, model 1) and 1.16 (95% CI, 1.02 to 1.32, model 2). Further subgroup analyses showed that severe pain was more associated with mortality for males and more educated individuals, with adjusted hazard ratios of 1.29 (95% CI, 1.08 to 1.55, model 2) and 1.62 (95% CI, 1.15 to 2.28, model 2), respectively.
CONCLUSIONS
Pain showed a statistically significant relationship with mortality risk. Family members or medical staff should pay proper attention to pain, particularly severe pain in males and highly educated individuals.
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Summary
Korean summary
우리나라의 고령인구와 만성질환의 증가가 가속화됨에 따라, 통증의 문제를 겪는 인구가 증가하고 통증의 사회경제적 영향도 커지고 있어 통증에 대한 엄밀한 분석이 요구된다. 본 연구는 통증을 주로 겪는 중·고령층을 대상으로 생존분석을 통해, 통증이 객관적 지표인 사망위험과 유의미하게 관련이 있음을 보였다. 따라서 환자의 통증 표현은, 특히 남성과 고학력자의 심한 통증 표현은, 사망과 관련이 있는 중요한 지표로 관리될 필요가 있으며 적절한 정책적 접근이 요구된다.
Key Message
With the increasing elderly population with chronic disease, understanding pain and designing appropriate policy interventions to it have become crucial. This study showed that pain had a statistically significant relationship with mortality risk, thus proper attention should be paid to it.
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Citations
Citations to this article as recorded by
- Sex-specific effects of neuropathic pain on long-term pain behavior and mortality in mice
Magali Millecamps, Susana G. Sotocinal, Jean-Sebastien Austin, Laura S. Stone, Jeffrey S. Mogil
Pain.2023; 164(3): 577. CrossRef - Spécificités de la prise en charge de la douleur chez la personne âgée
G. Pickering
Bulletin de l'Académie Nationale de Médecine.2023; 207(5): 661. CrossRef
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Demographic and epidemiological characteristics of scorpion envenomation and daily forecasting of scorpion sting counts in Touggourt, Algeria
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Kaouthar Boubekeur, Mohamed L’Hadj, Schehrazad Selmane
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Epidemiol Health. 2020;42:e2020050. Published online July 6, 2020
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DOI: https://doi.org/10.4178/epih.e2020050
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9,693
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Abstract
PDFSupplementary Material
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Abstract
OBJECTIVES
This study was conducted to provide better insights into the demographic and epidemiological characteristics of scorpion envenomation in an endemic area in Algeria and to identify the model that best predicted daily scorpion sting counts.
METHODS
Daily sting data from January 1, 2013 to August 31, 2016 were extracted from questionnaires designed to elicit information on scorpion stings from the two emergency medical service providers in Touggourt, Algeria. Count regression models were applied to the daily sting data.
RESULTS
A total of 4,712 scorpion sting cases were documented, of which 70% occurred in people aged between 10 years and 49 years. The male-to-female ratio was 1.3. The upper and lower limbs were the most common locations of scorpion stings (90.4% of cases). Most stings (92.8%) were mild. The percent of people stung inside dwellings was 68.8%. The hourly distribution of stings showed a peak between 10:00 a.m. and 11:00 a.m. The daily number of stings ranged from 0 to 24. The occurrence of stings was highest on Sundays. The incidence of scorpion stings increased sharply in the summer. The mean annual incidence rate was 542 cases per 100,000 inhabitants. The fitted count regression models showed that a negative binomial hurdle model was appropriate for forecasting daily stings in terms of temperature and relative humidity, and the fitted data agreed considerably with the actual data.
CONCLUSIONS
This study showed that daily scorpion sting data provided meaningful insights; and the negative binomial Hurdle model was preferable for predicting daily scorpion sting counts.
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Summary
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Ebola virus disease outbreak in Korea: use of a mathematical model and stochastic simulation to estimate risk
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Youngsuk Ko, Seok-Min Lee, Soyoung Kim, Moran Ki, Eunok Jung
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Epidemiol Health. 2019;41:e2019048. Published online November 24, 2019
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DOI: https://doi.org/10.4178/epih.e2019048
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11,467
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208
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Abstract
Summary
PDFSupplementary Material
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Abstract
OBJECTIVES
According to the World Health Organization, there have been frequent reports of Ebola virus disease (EVD) since the 2014 EVD pandemic in West Africa. We aim to estimate the outbreak scale when an EVD infected person arrives in Korea.
METHODS
Western Africa EVD epidemic mathematical model SEIJR or SEIJQR was modified to create a Korean EVD outbreak model. The expected number of EVD patients and outbreak duration were calculated by stochastic simulation under the scenarios of Best case, Diagnosis delay, and Case missing.
RESULTS
The 2,000 trials of stochastic simulation for each scenario demonstrated the following results: The possible median number of patients is 2 and the estimated maximum number is 11 when the government intervention is proceeded immediately right after the first EVD case is confirmed. With a 6-day delay in diagnosis of the first case, the median number of patients becomes 7, and the maximum, 20. If the first case is missed and the government intervention is not activated until 2 cases of secondary infection occur, the median number of patients is estimated at 15, and the maximum, at 35.
CONCLUSIONS
Timely and rigorous diagnosis is important to reduce the spreading scale of infection when a new communicable disease is inflowed into Korea. Moreover, it is imperative to strengthen the local surveillance system and diagnostic protocols to avoid missing cases of secondary infection.
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Summary
Korean summary
본 연구는 수학적 모델과 확률 시뮬레이션 기법을 이용하여 국내에 유입되지 않았던 에볼라바이러스병(EVD)의 확산 위험도를 정량적으로 예측하는 첫 번째 연구이다. 또한 이 연구를 통해 에볼라바이러스병 환자의 유입 시 발생 가능한 진단 지연 혹은 유입 미인지 상황을 가정하여 발생할 수 있는 2차 감염자 수 및 감염 종식까지의 기간을 계산했고 에볼라바이러스 유입 대비 실시간모니터링의 중요성과 확산 시 상황에 따른 최대 일일 환자수를 합리적으로 제시할 수 있다.
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Citations
Citations to this article as recorded by
- Estimating the Transmission Risk of COVID-19 in Nigeria: A Mathematical Modelling Approach
Irany FA, Akwafuo SE, Abah T, Mikler AR
Journal of Health Care and Research.2020; 1(3): 135. CrossRef
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Factors associated with mortality from tuberculosis in Iran: an application of a generalized estimating equation-based zero-inflated negative binomial model to national registry data
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Fatemeh Sarvi, Abbas Moghimbeigi, Hossein Mahjub, Mahshid Nasehi, Mahmoud Khodadost
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Epidemiol Health. 2019;41:e2019032. Published online July 9, 2019
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DOI: https://doi.org/10.4178/epih.e2019032
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11,629
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Abstract
OBJECTIVES
Tuberculosis (TB) is a global public health problem that causes morbidity and mortality in millions of people per year. The purpose of this study was to examine the relationship of potential risk factors with TB mortality in Iran.
METHODS
This cross-sectional study was performed on 9,151 patients with TB from March 2017 to March 2018 in Iran. Data were gathered from all 429 counties of Iran by the Ministry of Health and Medical Education and Statistical Center of Iran. In this study, a generalized estimating equation-based zero-inflated negative binomial model was used to determine the effect of related factors on TB mortality at the community level. For data analysis, R version 3.4.2 was used with the relevant packages.
RESULTS
The risk of mortality from TB was found to increase with the unemployment rate (βˆ=0.02), illiteracy (βˆ=0.04), household density per residential unit (βˆ=1.29), distance between the center of the county and the provincial capital (βˆ=0.03), and urbanization (βˆ=0.81). The following other risk factors for TB mortality were identified: diabetes (βˆ=0.02), human immunodeficiency virus infection (βˆ=0.04), infection with TB in the most recent 2 years (βˆ=0.07), injection drug use (βˆ=0.07), long-term corticosteroid use (βˆ=0.09), malignant diseases (βˆ=0.09), chronic kidney disease (βˆ=0.32), gastrectomy (βˆ=0.50), chronic malnutrition (βˆ=0.38), and a body mass index more than 10% under the ideal weight (βˆ=0.01). However, silicosis had no effect.
CONCLUSIONS
The results of this study provide useful information on risk factors for mortality from TB.
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Summary
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Application of a non-parametric non-mixture cure rate model for analyzing the survival of patients with colorectal cancer in Iran
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Mehdi Azizmohammad Looha, Mohamad Amin Pourhoseingholi, Maryam Nasserinejad, Hadis Najafimehr, Mohammad Reza Zali
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Epidemiol Health. 2018;40:e2018045. Published online September 17, 2018
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DOI: https://doi.org/10.4178/epih.e2018045
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10,607
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209
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5
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3
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Abstract
PDF
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Abstract
OBJECTIVES
Colorectal cancer (CRC) patients are considered to have been cured when the mortality rate of individuals with the disease returns to the same level as expected in the general population. This study aimed to assess the impact of various risk factors on the cure fraction of CRC patients using a real dataset of Iranian CRC patients with a non-mixture non-parametric cure model.
METHODS
This study was conducted on the medical records of 512 patients who were definitively diagnosed with CRC at Taleghani Hospital, Tehran, Iran from 2001 to 2007. A non-mixture non-parametric cure rate model was applied to the data after using stepwise selection to identify the risk factors of CRC.
RESULTS
For non-cured cases, the mean survival time was 1,243.83 days (95% confidence interval [CI], 1,174.65 to 1,313.00) and the median survival time was 1,493.00 days (95% CI, 1,398.67 to 1,587.33). The 1- and 3-year survival rates were 92.9% (95% CI, 91.0 to 95.0) and 73.4% (95% CI, 68.0 to 79.0), respectively. Pathologic stage T1 of the primary tumor (estimate=0.58; p=0.013), a poorly differentiated tumor (estimate=1.17; p<0.001), a body mass index (BMI) between 18.6 and 24.9 kg/m2 (estimate=−0.60; p=0.04), and a BMI between 25.0 and 29.9 kg/m2 (estimate=−1.43; p<0.001) had significant impacts on the cure fraction of CRC in the multivariate analysis. The proportion of cured patients was 64.1% (95% CI, 56.7 to 72.4).
CONCLUSIONS
This study found that the pathologic stage of the primary tumor, tumor grade, and BMI were potential risk factors that had an impact on the cure fraction. A non-mixture non-parametric cure rate model provides a flexible framework for accurately determining the impact of risk factors on the long-term survival of patients with CRC.
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- Post‐diagnosis adiposity and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta‐analysis
Nerea Becerra‐Tomás, Georgios Markozannes, Margarita Cariolou, Katia Balducci, Rita Vieira, Sonia Kiss, Dagfinn Aune, Darren C. Greenwood, Laure Dossus, Ellen Copson, Andrew G. Renehan, Martijn Bours, Wendy Demark‐Wahnefried, Melissa M. Hudson, Anne M. Ma
International Journal of Cancer.2024;[Epub] CrossRef - Assessment of prognostic factors in long-term survival of male and female patients with colorectal cancer using non-mixture cure model based on the Weibull distribution
Mehdi Azizmohammad Looha, Elaheh Zarean, Fatemeh Masaebi, Mohamad Amin Pourhoseingholi, Mohamad Reza Zali
Surgical Oncology.2021; 38: 101562. CrossRef - Actual survival after resection of primary colorectal cancer: results from a prospective multicenter study
Inge van den Berg, Robert R. J. Coebergh van den Braak, Jeroen L. A. van Vugt, Jan N. M. Ijzermans, Stefan Buettner
World Journal of Surgical Oncology.2021;[Epub] CrossRef
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Using the capture-recapture method to estimate the human immunodeficiency virus-positive population
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Jalal Poorolajal, Younes Mohammadi, Farzad Farzinara
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Epidemiol Health. 2017;39:e2017042. Published online October 10, 2017
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DOI: https://doi.org/10.4178/epih.e2017042
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13,274
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10
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Abstract
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Abstract
OBJECTIVES
The capture-recapture method was applied to estimate the number of human immunodeficiency virus (HIV)-positive individuals not registered with any data sources.
METHODS
This cross-sectional study was conducted in Lorestan Province, in the west of Iran, in 2016. Three incomplete sources of HIV-positive individuals, with partially overlapping data, were used, including: (a) transfusion center, (b) volunteer counseling and testing centers (VCTCs), and (c) prison. The 3-source capture-recapture method, using a log-linear model, was applied for data analysis. The Akaike information criterion and the Bayesian information criterion were used for model selection.
RESULTS
Of the 2,456 HIV-positive patients registered in these 3 data sources, 1,175 (47.8%) were identified in transfusion center, 867 (35.3%) in VCTCs, and 414 (16.8%) in prison. After the exclusion of duplicate entries, 2,281 HIV-positive patients remained. Based on the capture-recapture method, 14,868 (95% confidence interval, 9,923 to 23,427) HIV-positive individuals were not identified in any of the registries. Therefore, the real number of HIV-positive individuals was estimated to be 17,149, and the overall completeness of the 3 registries was estimated to be around 13.3%.
CONCLUSIONS
Based on capture-recapture estimates, a huge number of HIV-positive individuals are not registered with any of the provincial data sources. This is an urgent message for policymakers who plan and provide health care services for HIV-positive patients. Although the capture-recapture method is a useful statistical approach for estimating unknown populations, due to the assumptions and limitations of the method, the population size may be overestimated as it seems possible in our results.
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Summary
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- Improving HIV stigma in the marginalized population in Khorramabad, Iran: A single-blinded randomized, controlled educational trial using role-playing and lecturing
Mina Jomezadeh, Fereshteh Zamani-Alavijeh, Forugh Aleebrahim, Maryam Nasirian, Kavitha Saravu
PLOS Global Public Health.2023; 3(3): e0000689. CrossRef - Estimación de casos de VIH no diagnosticados en la región Cajamarca, Perú: vinculación probabilística entre bases de datos
Hans Ramón Quiroz-Ruiz, Omar Daniel Pairazamán-Quiroz, Diego Enrique Quiroz-Villanueva, Hernán Daniel Cornejo-Pacherres, Fiorella Nathalí Hernández-Palomino, Azucena Angélica Cruzado-Montero, Jorge Enrique Bazán-Mayra, Eduardo Miranda-Ulloa
Ciência & Saúde Coletiva.2023; 28(6): 1843. CrossRef - On some pitfalls of the log-linear modeling framework for capture-recapture studies in disease surveillance
Yuzi Zhang, Lin Ge, Lance A. Waller, Robert H. Lyles
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Goundappa K. Balasubramani, Mary Patricia Nowalk, Lloyd G. Clarke, Klancie Dauer, Fernanda Silveira, Donald B. Middleton, Mohamed Yassin, Richard K. Zimmerman
Influenza and Other Respiratory Viruses.2022; 16(2): 308. CrossRef - Using Capture–Recapture Methodology to Enhance Precision of Representative Sampling-Based Case Count Estimates
Robert H Lyles, Yuzi Zhang, Lin Ge, Cameron England, Kevin Ward, Timothy L Lash, Lance A Waller
Journal of Survey Statistics and Methodology.2022; 10(5): 1292. CrossRef - Population Size Estimation From Capture-Recapture Studies Using shinyrecap: Design and Implementation of a Web-Based Graphical User Interface
Anne F McIntyre, Ian E Fellows, Steve Gutreuter, Wolfgang Hladik
JMIR Public Health and Surveillance.2022; 8(4): e32645. CrossRef - Estimating the number of farms experienced foot and mouth disease outbreaks using capture-recapture methods
Chalutwan Sansamur, Anuwat Wiratsudakul, Arisara Charoenpanyanet, Veerasak Punyapornwithaya
Tropical Animal Health and Production.2021;[Epub] CrossRef - Epidemiologic characteristics of orthopedic surgical site infections and under-reporting estimation of registries using capture-recapture analysis
Niloufar Taherpour, Yadollah Mehrabi, Arash Seifi, Babak Eshrati, Seyed Saeed Hashemi Nazari
BMC Infectious Diseases.2021;[Epub] CrossRef - National and subnational size estimation of female sex workers in Ghana 2020: Comparing 3-source capture-recapture with other approaches
Chris Guure, Samuel Dery, Seth Afagbedzi, Waimar Tun, Sharon Stucker Weir, Silas Quaye, Augustine Ankomah, Kwasi Torpey, Georges Nguefack-Tsague
PLOS ONE.2021; 16(9): e0256949. CrossRef - A Review of Capture-recapture Methods and Its Possibilities in Ophthalmology and Vision Sciences
Pedro Lima Ramos, Inês Sousa, Rui Santana, William H Morgan, Keith Gordon, Julie Crewe, Amândio Rocha-Sousa, Antonio Filipe Macedo
Ophthalmic Epidemiology.2020; 27(4): 310. CrossRef - Size of the Adult HIV-Infected Population Adjusted for the Unreported AIDS Mortality in the Santa Catarina State, Brazil, 2008-2017
Larissa Hermes Thomas Tombini, Emil Kupek
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Methods
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Meta-analysis for genome-wide association studies using case-control design: application and practice
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Sungryul Shim, Jiyoung Kim, Wonguen Jung, In-Soo Shin, Jong-Myon Bae
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Epidemiol Health. 2016;38:e2016058. Published online December 18, 2016
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DOI: https://doi.org/10.4178/epih.e2016058
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18,013
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Abstract
Summary
PDFSupplementary Material
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Abstract
This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy–Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The ‘genhwcci’ and ‘metan’ commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the ‘metareg’ command of STATA should be conducted to evaluate related factors of heterogeneities.
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Summary
Korean summary
오늘날 활발히 수행되고 있는 유전체역학연구는 재현성의 문제, 대상자 크기의 한계 등으로 유전체 메타분석 연구가 요구되고 있다. 유전체 메타분석의 전반적인 수행 단계는 약물, 수술 등의 중개연구의 메타분석처럼 5 단계를 밟아 수행된다. 그러나, 유전체 메타분석은 3번째 과정에서 Hardy–Weinberg equilibrium (HWE) 검정과 4번째 과정에서 5가지 가능한 유전형 모델에 따라 메타분석이 이루어진다는 점에서 중개연구의 메타분석과 차이가 있다.
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Hilary Sito, Mohamad Ayub Khan Sharzehan, Md Asiful Islam, Shing Cheng Tan
British Journal of Biomedical Science.2024;[Epub] CrossRef - Recommendations for Statistical Reporting in Cardiovascular Medicine: A Special Report From the American Heart Association
Andrew D. Althouse, Jennifer E. Below, Brian L. Claggett, Nancy J. Cox, James A. de Lemos, Rahul C. Deo, Sue Duval, Rory Hachamovitch, Sanjay Kaul, Scott W. Keith, Eric Secemsky, Armando Teixeira-Pinto, Veronique L. Roger
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Toxicological Sciences.2020; 177(1): 27. CrossRef - Associations between TLR4 Polymorphisms and Open Angle Glaucoma: A Meta-Analysis
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Original Articles
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Diabetic peripheral neuropathy class prediction by multicategory support vector machine model: a cross-sectional study
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Maryam Kazemi, Abbas Moghimbeigi, Javad Kiani, Hossein Mahjub, Javad Faradmal
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Epidemiol Health. 2016;38:e2016011. Published online March 24, 2016
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DOI: https://doi.org/10.4178/epih.e2016011
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16,386
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Abstract
OBJECTIVES
Diabetes is increasing in worldwide prevalence, toward epidemic levels. Diabetic neuropathy, one of the most common complications of diabetes mellitus, is a serious condition that can lead to amputation. This study used a multicategory support vector machine (MSVM) to predict diabetic peripheral neuropathy severity classified into four categories using patients’ demographic characteristics and clinical features.
METHODS
In this study, the data were collected at the Diabetes Center of Hamadan in Iran. Patients were enrolled by the convenience sampling method. Six hundred patients were recruited. After obtaining informed consent, a questionnaire collecting general information and a neuropathy disability score (NDS) questionnaire were administered. The NDS was used to classify the severity of the disease. We used MSVM with both one-against-all and one-against-one methods and three kernel functions, radial basis function (RBF), linear, and polynomial, to predict the class of disease with an unbalanced dataset. The synthetic minority class oversampling technique algorithm was used to improve model performance. To compare the performance of the models, the mean of accuracy was used.
RESULTS
For predicting diabetic neuropathy, a classifier built from a balanced dataset and the RBF kernel function with a one-against-one strategy predicted the class to which a patient belonged with about 76% accuracy.
CONCLUSIONS
The results of this study indicate that, in terms of overall classification accuracy, the MSVM model based on a balanced dataset can be useful for predicting the severity of diabetic neuropathy, and it should be further investigated for the prediction of other diseases.
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Khadijeh Khalili Azar, Amirreza Mirzaei, Ali-Reza Babapour, Azita Fathnezhad-Kazemi
SAGE Open Medicine.2024;[Epub] CrossRef - Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes
Jingtong Huang, Andrea M. Yeung, David G. Armstrong, Ashley N. Battarbee, Jorge Cuadros, Juan C. Espinoza, Samantha Kleinberg, Nestoras Mathioudakis, Mark A. Swerdlow, David C. Klonoff
Journal of Diabetes Science and Technology.2023; 17(1): 224. CrossRef - A Machine Learning-Based Severity Prediction Tool for the Michigan Neuropathy Screening Instrument
Fahmida Haque, Mamun B. I. Reaz, Muhammad E. H. Chowdhury, Mohd Ibrahim bin Shapiai, Rayaz A. Malik, Mohammed Alhatou, Syoji Kobashi, Iffat Ara, Sawal H. M. Ali, Ahmad A. A. Bakar, Mohammad Arif Sobhan Bhuiyan
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Dalton Kambale Munyambalu, Idania Hildago, Yves Tibamwenda Bafwa, Charles Abonga Lagoro, Franck Katembo Sikakulya, Bienfait Mumbere Vahwere, Ephraim Dafiewhare, Lazaro Martinez, Fardous Abeya Charles
Frontiers in Clinical Diabetes and Healthcare.2023;[Epub] CrossRef - Study on risk factors of diabetic peripheral neuropathy and establishment of a prediction model by machine learning
Xiaoyang Lian, Juanzhi Qi, Mengqian Yuan, Xiaojie Li, Ming Wang, Gang Li, Tao Yang, Jingchen Zhong
BMC Medical Informatics and Decision Making.2023;[Epub] CrossRef - Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts
Georgios Baskozos, Andreas C. Themistocleous, Harry L. Hebert, Mathilde M. V. Pascal, Jishi John, Brian C. Callaghan, Helen Laycock, Yelena Granovsky, Geert Crombez, David Yarnitsky, Andrew S. C. Rice, Blair H. Smith, David L. H. Bennett
BMC Medical Informatics and Decision Making.2022;[Epub] CrossRef - Predictors Associated with Type 2 Diabetes Mellitus Complications over Time: A Literature Review
Marwa Elsaeed Elhefnawy, Siti Maisharah Sheikh Ghadzi, Sabariah Noor Harun
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Eiichiro Kanda, Atsushi Suzuki, Masaki Makino, Hiroo Tsubota, Satomi Kanemata, Koichi Shirakawa, Toshitaka Yajima
Scientific Reports.2022;[Epub] CrossRef - Prediction of Diabetic Neuropathy Using Machine Learning Techniques
Jung Keun Hyun
The Journal of Korean Diabetes.2022; 23(4): 238. CrossRef - Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data
Mathieu Ravaut, Hamed Sadeghi, Kin Kwan Leung, Maksims Volkovs, Kathy Kornas, Vinyas Harish, Tristan Watson, Gary F. Lewis, Alanna Weisman, Tomi Poutanen, Laura Rosella
npj Digital Medicine.2021;[Epub] CrossRef - Performance Analysis of Conventional Machine Learning Algorithms for Diabetic Sensorimotor Polyneuropathy Severity Classification
Fahmida Haque, Mamun Bin Ibne Reaz, Muhammad Enamul Hoque Chowdhury, Geetika Srivastava, Sawal Hamid Md Ali, Ahmad Ashrif A. Bakar, Mohammad Arif Sobhan Bhuiyan
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Md. Maniruzzaman, Md. Merajul Islam, Md. Jahanur Rahman, Md. Al Mehedi Hasan, Jungpil Shin
Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2021; 15(5): 102263. CrossRef - Prediction of Diabetic Sensorimotor Polyneuropathy Using Machine Learning Techniques
Dae Youp Shin, Bora Lee, Won Sang Yoo, Joo Won Park, Jung Keun Hyun
Journal of Clinical Medicine.2021; 10(19): 4576. CrossRef - T1DMicro: A Clinical Risk Calculator for Type 1 Diabetes Related Microvascular Complications
Paul Minh Huy Tran, Eileen Kim, Lynn Kim Hoang Tran, Bin Satter Khaled, Diane Hopkins, Melissa Gardiner, Jennifer Bryant, Risa Bernard, John Morgan, Bruce Bode, John Chip Reed, Jin-Xiong She, Sharad Purohit
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Negar Asaad Sajadi, Hossein Mahjub, Shiva Borzouei, Maryam Farhadian
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Oleg Metsker, Kirill Magoev, Alexey Yakovlev, Stanislav Yanishevskiy, Georgy Kopanitsa, Sergey Kovalchuk, Valeria V. Krzhizhanovskaya
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Estimation of the Frequency of Intravenous Drug Users in Hamadan City, Iran, Using the Capture-recapture Method
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Salman Khazaei, Jalal Poorolajal, Hossein Mahjub, Nader Esmailnasab, Mohammad Mirzaei
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Epidemiol Health. 2012;34:e2012006. Published online October 31, 2012
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DOI: https://doi.org/10.4178/epih/e2012006
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Abstract
<sec><title>OBJECTIVES</title><p>The number of illicit drug users is prone to underestimation. This study aimed to use the capture-recapture method as a statistical procedure for measuring the prevalence of intravenous drug users (IDUs) by estimating the number of unknown IDUs not registered by any of the registry centers.</p></sec><sec><title>METHODS</title><p>This study was conducted in Hamadan City, the west of Iran, in 2012. Three incomplete data sources of IDUs, with partial overlapping data, were assessed including: (a) Volunteer Counseling and Testing Centers (VCTCs); (b) Drop in Centers (DICs); and (c) Outreach Teams (ORTs). A log-linear model was applied for the analysis of three-sample capture-recapture results. Two information criteria were used for model selection including Akaike's Information Criterion and the Bayesian Information Criterion.</p></sec><sec><title>RESULTS</title><p>Out of 1,478 IDUs registered by three centers, 48% were identified by VCTCs, 32% by DICs, and 20% by ORTs. After exclusion of duplicates, 1,369 IDUs remained. According to our findings, there were 9,964 (95% CI, 6,088 to 17,636) IDUs not identified by any of the centers. Hence, the real number of IDUs is expected to be 11,333. Based on these findings, the overall completeness of the three data sources was around 12% (95% CI, 7% to 18%).</p></sec><sec><title>CONCLUSION</title><p>There was a considerable number of IDUs not identified by any of the centers. Although the capture-recapture method is a useful and practical approach for estimating unknown populations, due to the assumptions and limitations of the method, the results must be interpreted with caution.</p></sec>
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- The prevalence of opioid use disorder in Kentucky’s counties: A two-year multi-sample capture-recapture analysis
Katherine Thompson, Joshua A. Barocas, Chris Delcher, Jungjun Bae, Lindsey Hammerslag, Jianing Wang, Redonna Chandler, Jennifer Villani, Sharon Walsh, Jeffery Talbert
Drug and Alcohol Dependence.2023; 242: 109710. CrossRef - Estimating the Population Size of Female Sex Worker Population in Tehran, Iran: Application of Direct Capture–Recapture Method
Manoochehr Karami, Salman Khazaei, Jalal Poorolajal, Alireza Soltanian, Mansour Sajadipoor
AIDS and Behavior.2017; 21(8): 2394. CrossRef - Using the capture-recapture method to estimate the human immunodeficiency virus-positive population
Jalal Poorolajal, Younes Mohammadi, Farzad Farzinara
Epidemiology and Health.2017; 39: e2017042. CrossRef - Estimation of perinatal mortality rate for institutional births in Rajasthan state, India, using capture-recapture technique
P. K. Mony, B. Varghese, T. Thomas
BMJ Open.2015; 5(3): e005966. CrossRef - Estimating the size of the population of persons who inject drugs in the island of Montréal, Canada, using a six-source capture–recapture model
Pascale Leclerc, Alain C. Vandal, Aïssatou Fall, Julie Bruneau, Élise Roy, Suzanne Brissette, Chris Archibald, Nelson Arruda, Carole Morissette
Drug and Alcohol Dependence.2014; 142: 174. CrossRef - Heterogeneity and behavioral response in continuous time capture–recapture, with application to street cannabis use in Italy
Alessio Farcomeni, Daria Scacciatelli
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