ABSTRACT
The spread of COVID-19, apart from being influenced by specific pathogenic factors, is also influenced by population structure and mobility. This study was conducted to develop a forecasting model for the increase in COVID-19 cases due to variations in the holiday calendar and the sun's distance to the earth. This study uses secondary data taken from the East Java Provincial Health Office in collaboration with the East Java Province COVID-19 Task Force. This study uses two independent variables: the Calendar Variation in 2020 and 2021 (X1);The Sun-Earth Distance (X2) and dependent variable (Y) is the Daily Case of COVID-19 in East Java Province from March 2020 to June 2021. The process of data analysis is carried out by analyzing time series data and building a forecasting model with a symbolic time series prognosis approach. The analysis process is carried out using Heuristic Lab 3.3 software. Based on the results of this study, it can be concluded that variations in the holiday calendar and the sun-earth distance have a strong influence on daily cases of COVID-19. The symbolic time series prognosis model obtained has an accuracy rate of up to 90.04% on training data and 82.14% on testing data. © 2023 WITPress. All rights reserved.
ABSTRACT
BACKGROUND: The fluctuating COVID-19 cases among the pregnant women’s population encountered increased of cases and maternal mortality. AIM: This research aimed to describe the case of maternal deaths caused by COVID-19. CASE REPORT: We present nine serial cases of maternal death caused by COVID-19 who were admitted to Dr. Soetomo General Academic Hospital for 14 days in June. We found 32 positive COVID-19 obstetric cases and reported nine maternal deaths with a fatality rate of up to 28%. Seven of nine patients had reverse transcription-polymerase chain reaction–confirmed SARS-CoV-2 infection, while two had a positive antigen swab. Half of the patients ≥35 years old, and five of nine patients had Class I obesity as preexisting comorbidity. This study reported the death of pregnant woman at their 2nd trimester and 3rd trimester presenting infected by severe COVID-19. The usual symptoms are dyspnea, cough, fever, and decreased consciousness. The result of chest X-ray examination among eight patients showed bilateral pneumonia. Most of cases were referrals from a secondary hospital due to overload hospital capacity. Three patients were directly transferred to the tertiary hospital without receiving initial treatment. Eight of 9 patients (88.9%) were transferred to intensive care unit and intubated due to low oxygen saturation. CONCLUSION: In conclusion, the limited hospital facility and lack of intensive care capacity for obstetric cases during the second wave of the COVID-19 pandemic may enhance the probability of mortality and morbidity in pregnant women infected by COVID-19.
ABSTRACT
Currently the world is experiencing a Corona Virus Disease (Covid-19) pandemic which attacks the respiratory tract and spreads very quickly to various countries including Indonesia, so the World Health Organization (WHO) has declared Covid-19 as a pandemic. To overcome this pandemic, experts in the medical field also intervened by making vaccinations to strengthen human immunity against the Covid virus. This sentiment analysis was carried out to see opinions on the object, namely the existence of a Covid-19 vaccine. Data collection by crawling data with the keyword 'Covid Vaccine'. The method that will be used is the Support Vector Machine (SVM). The analysis was carried out by comparing the classification accuracy values of the two SVM kernel functions, namely linear and Radial Basic Function (RBF). The results of the study obtained positive sentiment of 43.5%, negative of 19.1%, and neutral of 37.4%. Then the evaluation of the system using the confusion matrix obtained an accuracy value for the linear kernel of 79.15%, a precision value of 77.31%, and a recall value of 78.09%. While the RBF kernel has an accuracy of 84.25%, a precision value of 83.67%, and a recall value of 81.99%. While the cross validation obtained the optimum value at $\mathrm{k}=1$ with an accuracy value of 80.18% for the linear kernel and 85.88% for the RBF kernel. So the RBF kernel has a higher accuracy than the linear kernel. © 2021 IEEE.
ABSTRACT
Background: The emergency, labor and delivery conditions in obstetric cases need a clinical decision in a timely manner. The identification of Covid-19 especially in asymptomatic obstetric cases with ease and rapid antibody test need further investigation. Objective: To analyze the usability and performance of rapid antibody test in obstetric cases. Methods: Case control study using medical record on Covid-19 obstetric cases over 9 months with paired nasopharyngeal reverse transcriptase polymerase chain reaction severe acute respiratory syndrome coronavirus 2 and rapid antibody test results. Results: There were 92 Covid-19 obstetric cases (incidence: 17.4%) and 210 reactive rapid antibody test (seroprevalence: 39.6%). The sensitivity, specificity, positive predictive value and negative predictive value of rapid antibody tests was 89%, 24%, 40%, 80%. Symptomatic cases have lower sensitivity (73% vs. 96%) and higher specificity (48% vs. 20%). The presence of Covid-19 symptoms (p<0.05) and reactive rapid antibody test (p<0.001) were associated with Covid-19. Rapid antibody test will identify larger Covid-19 obstetric cases compare with the presence of symptom only (89.4% vs. 27.7%. Conclusion: Screening by rapid antibody test had a high sensitivity but low specificity. This test will identify more Covid-19 cases compared by symptoms only due to majority asymptomatic obstetric cases. This simple, cheap and rapid antibody test still has a place in initial screening to help identify Covid-19 in areas with widespread transmission and has limited capacity to carry out universal screening.
ABSTRACT
Background: Covid-19 infection in vulnerable obstetric patients still requires a lot of re-search, especially in developing countries to help determine the best policy to manage it. Objective: To analyze the characteristic of Covid-19 infection in obstetric patients. Methods: In an East Java tertiary Covid-19 referral hospital, a case control analysis was conducted using medical records on obstetric cases of Covid-19 infection from March until November 2021. Results: Covid-19 was identified in 109 cases (9.3%) from 1170 patients who came to our obstetric room. Majority came in pregnancy state with 76% and had delivered 93.6%. Most patients were as-ymptomatic (68.8%) with minimal contact history (2.8%). Comorbidity found in 41.3% cases, obesity and hypertension in pregnancy dominated the cases. Symptomatic cases were associated with lower gestational age (p=0,005) and birthweight (p=0,015), low lymphocyte count (p=0,006), abnormal chest X-Ray (p<0,001), intensive care admission (p=0,002) and maternal death (p<0,001), while asymptomatic cases were associated with more reactive antibody test (p=0,002). Conclusion: There were a high number of Covid-19 obstetric cases with the majority as-ymptomatic and came for delivery. Significantly higher reactive antibody tests in asymptomatic cases may aid Covid-19 identification. Covid-19 symptoms should be given more consideration, because they are linked to a lower gestational age, birth weight, poor clinical parameters, the need for intensive care, and maternal mortality. © 2021, Yerevan State Medical University. All rights reserved.
ABSTRACT
Background: Covid-19 infection in vulnerable obstetric patients still requires a lot of research, especially in developing countries to help determine the best policy to manage it. Objective: To analyze the characteristic of Covid-19 infection in obstetric patients. Methods: In an East Java tertiary Covid-19 referral hospital, a case control analysis was conducted using medical records on obstetric cases of Covid-19 infection from March until November 2021. Results: Covid-19 was identified in 109 cases (9.3%) from 1170 patients who came to our obstetric room. Majority came in pregnancy state with 76% and had delivered 93.6%. Most patients were asymptomatic (68.8%) with minimal contact history (2.8%). Comorbidity found in 41.3% cases, obesity and hypertension in pregnancy dominated the cases. Symptomatic cases were associated with lower gestational age (p=0,005) and birthweight (p=0,015), low lymphocyte count (p=0,006), abnormal chest X-Ray (p<0,001), intensive care admission (p=0,002) and maternal death (p<0,001), while asymptomatic cases were associated with more reactive antibody test (p=0,002). Conclusion: There were a high number of Covid-19 obstetric cases with the majority asymptomatic and came for delivery. Significantly higher reactive antibody tests in asymptomatic cases may aid Covid-19 identification. Covid-19 symptoms should be given more consideration, because they are linked to a lower gestational age, birth weight, poor clinical parameters, the need for intensive care, and maternal mortality.
ABSTRACT
The contribution of fisheries to the national GDP had increased from 2.32% in 2014 to 2.60% in 2018. However, in 2020, the threat of the Covid-19 pandemic emerged, which hit all sectors of the economy, including the fisheries sector. Many communities, especially coastal fishing communities, are complaining about economic hardship. Income has fallen dramatically because people’s purchasing power has fallen significantly. Based on these problems, this research was conducted to build a fishers’ income prediction model. This research took a case study on fishers in Karanggongso District Trenggalek by surveying 50 fishing households. There were 12 predictors variables, namely Boat Type (X1), Price Boat (X2), Age of the Boat (X3), Boat Power (X4), Machine Price (X5), Engine Life (X6), Fishing Equipment Price (X7), Fishing Gear Life (X8), Cool Box (X9), Trip/week (X10), Average Hours/trip (X11), and Total Expenditures/week (X12). The response variable is Income Per Week (Y). Data analysis was done by using multiple linear regression analysis and flexible modelling with a machine learning approach. Based on the results of the analysis, a multiple linear regression model had an accuracy level of R 2 = 70.5% and MSE = 1.086 × 1018 with the boat price was the most dominant influence on fishers’ income. While flexible modelling has an accuracy level of R 2 = 85.2% and MSE = 3.308 × 1014. From this research, it was proven that the flexible model had a higher level of accuracy than the linear regression model. Also, the flexible model obtained the nonlinear effect on the number of cool boxes and the fishing gear life.
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Background: COVID-19 identification in obstetric emergency cases with limited resources is problematic, particularly in asymptomatic cases. Aim: To examine the screening strategies of COVID-19 obstetric emergency cases in low-resource health care settings. Method: A retrospective cohort design was carried out on patients with COVID-19 positive screening results. It was assessed based on symptoms, contact history, lymphocytopenia, chest X-rays, and rapid antibody tests compared to RT-PCR results SARS-COV-2. Result: Out of the 190 cases that came to the delivery room, the staff suspected 69 COVID-19 cases (36.3%) through the first screening protocol. Positive SARS-COV-2 RT-PCR was found in 23 cases with a majority asymptomatic (52.2%). The percentages of sensitivity and specificity from the parameters as follow: 48% and 74% in COVID-19 symptoms (febris or respiratory symptoms);9% and 100% in contact history;22% and 83% in lymphocytopenia;52% and 48% in chest x-ray;78% and 30% in rapid antibody test. Rapid antibody tests have the highest sensitivity to increase the identification of 12 asymptomatic cases. Conclusion: Other screening beyond symptoms and contact history such as lymphocytopenia, chest x-ray, and rapid antibody test can improve the identification, especially for asymptomatic cases in areas with the limited testing ability and high Covid-19 transmission. © 2021 Lahore Medical And Dental College. All rights reserved.