Objectives The co-occurrence of tuberculosis (TB) and diabetes mellitus presents a significant global health challenge, marked by a bidirectional relationship. This study aims to evaluate the effectiveness of the tuberculosis predictive index (TPI) score, developed by Isfandiari et al., in predicting TB occurrence among individuals living with type 2 diabetes mellitus. Methods: A case-control study was conducted using primary data collected through questionnaires administered to individuals with type 2 diabetes mellitus, with and without pulmonary TB, at the internal medicine outpatient clinic of Fatmawati General Hospital from June to August 2024. The study compared TPI scores between those with type 2 diabetes mellitus who had TB and those who did not. Results: TPI scores were significantly associated with TB risk. Individuals with both type 2 diabetes mellitus and TB had a 6.8-fold higher risk (95% confidence interval [CI], 2.6–17.6; p<0.001) than those without TB. Further chi-square analysis identified three significant risk factors: individuals with type 2 diabetes mellitus exhibiting TB-like symptoms had a 13.3-fold increased TB risk (95% CI, 5.1–34.3; p<0.001); those with a body mass index below 18.5 kg/m² had a 3.3-fold higher risk (95% CI, 1.0–11.0; p=0.039); and those living in poorly ventilated homes (ventilation ≤10%) had a 3.2-fold higher risk (95% CI, 1.0–9.8; p=0.035). Conclusion: This study demonstrates that individuals with type 2 diabetes mellitus who developed TB had significantly higher TPI scores, corresponding to a 6.8-fold increased risk compared to their counterparts without TB. The TPI score may serve as a valuable tool for predicting TB risk among populations living with type 2 diabetes mellitus.
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Artificial intelligence and biohealth: the Republic of Korea’s emerging priorities in health care R&D Jong-Koo Lee Osong Public Health and Research Perspectives.2025; 16(4): 309. CrossRef
Objectives This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy.
Methods The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites.
Results Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital.
Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.
<sec>
<title>Objectives</title>
<p>This study presents the development and validation of a risk assessment program of highly pathogenic avian influenza (HPAI). This program was developed by the Korean government (Animal and Plant Quarantine Agency) and a private corporation (Korea Telecom, KT), using a national database (Korean animal health integrated system, KAHIS).</p></sec>
<sec>
<title>Methods</title>
<p>Our risk assessment program was developed using the multilayer perceptron method using R Language. HPAI outbreaks on 544 poultry farms (307 with H5N6, and 237 with H5N8) that had available visit records of livestock-related vehicles amongst the 812 HPAI outbreaks that were confirmed between January 2014 and June 2017 were involved in this study.</p></sec>
<sec>
<title>Results</title>
<p>After 140,000 iterations without drop-out, a model with 3 hidden layers and 10 nodes per layer, were selected. The activation function of the model was hyperbolic tangent. Precision and recall of the test gave F1 measures of 0.41, 0.68 and 0.51, respectively, at validation. The predicted risk values were higher for the “outbreak” (average ± SD, 0.20 ± 0.31) than “non-outbreak” (0.18 ± 0.30) farms (<italic>p</italic> < 0.001).</p></sec>
<sec>
<title>Conclusion</title>
<p>The risk assessment model developed was employed during the epidemics of 2016/2017 (pilot version) and 2017/2018 (complementary version). This risk assessment model enhanced risk management activities by enabling preemptive control measures to prevent the spread of diseases.</p></sec>
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<sec>
<title>Objectives</title>
<p>This study aims to evaluate the risk assessments of coronavirus 2019 (COVID-19) in the Korea Centers for Disease Control and Prevention (KCDC), from the point of detection to the provision of basic information to the relevant public health authorities.</p></sec>
<sec>
<title>Methods</title>
<p>To estimate the overall risk of specific public health events, probability, and impact at the country-level were evaluated using available information. To determine the probability of particular public health events, the risk of importation and risk of transmission were taken into consideration. KCDC used 5 levels (“very low,” “low,” “moderate,” “high,” and “very high”) for each category and overall risk was eventually decided.</p></sec>
<sec>
<title>Results</title>
<p>A total of 8 risk assessments were performed on 8 separate occasions between January 8<sup>th</sup> to February 28<sup>th</sup>, 2020, depending on the detection and report of COVID-19 cases in other countries. The overall risk of the situation in each assessment increased in severity over this period: “low” (first), “moderate” (second), “high” (third), “high” (fourth), “high” (fifth), “high” (sixth), “high” (seventh), and “very high” (eighth).</p></sec>
<sec>
<title>Conclusion</title>
<p>The KCDC’s 8 risk assessments were utilized to activate national emergency response mechanisms and eventually prepare for the pandemic to ensure the containment and mitigation of COVID-19 with non-pharmaceutical public health measures.</p></sec>
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<sec>
<title>Objectives</title>
<p>Aflatoxins are a category of poisonous compounds found in most plants, milk and dairy products. The present research was carried out to detect the presence of aflatoxin M<sub>1</sub> (AFM<sub>1</sub>) in samples of milk collected from Hamadan province, Iran.</p></sec>
<sec>
<title>Methods</title>
<p>Twenty five samples of ultra-high temperature (UHT) and 63 samples of pasteurized milk were collected and the amount of AFM<sub>1</sub> was measured by an Enzyme-Linked Immunosorbent Assay method. In addition, the estimated daily intake (EDI) and hazard index (HI) of AFM<sub>1</sub> was determined by the following equations:(EDI= mean concentration of AFM<sub>1</sub> × daily consumption of milk/body weight; HI= EDI/Tolerance Daily Intake).</p></sec>
<sec>
<title>Results</title>
<p>AFM<sub>1</sub> was detected in 21 (84%) UHT milk samples and in 55 (87.30%) pasteurized milk samples. Seven (28%) samples of UHT and 21 (33.33%) pasteurized milk samples had higher AFM<sub>1</sub> content than the limit allowed in the European Union and Iranian National Standard Limits (0.05 μg/kg). None of the samples exceeded the US Food and Drug Administration limit (0.5 μg/kg) for AFM<sub>1</sub>. EDI and HI for AM<sub>1</sub> through milk were 0.107 ng/kg body weight/day, and 0.535, respectively.</p></sec>
<sec>
<title>Conclusion</title>
<p>A significant percentage of milk produced by different factories in Iran (84% of UHT and 87.3% of pasteurized milk) was contaminated with AFM<sub>1</sub>. Therefore, more control and monitoring of livestock feeding in dairy companies may help reduce milk contamination with AFM<sub>1</sub>. As the HI value was lower than 1, it can be assumed that there was no risk of developing liver cancer due to milk consumption.</p></sec>
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