Predicting Mortality in Hospitalized COVID-19 Patients in Zambia: An Application of Machine Learning

The coronavirus disease 2019 (COVID-19) has wreaked havoc globally, resulting in millions of cases and deaths. The objective of this study was to predict mortality in hospitalized COVID-19 patients in Zambia using machine learning (ML) methods based on factors that have been shown to be predictive of mortality and thereby improve pandemic preparedness. This research employed seven powerful ML models that included decision tree (DT), random forest (RF), support vector machines (SVM), logistic regression (LR), Naïve Bayes (NB), gradient boosting (GB), and XGBoost (XGB). These classifiers were trained on 1,433 hospitalized COVID-19 patients from various health facilities in Zambia. The performances achieved by these models were checked using accuracy, recall, F1-Score, area under the receiver operating characteristic curve (ROC_AUC), area under the precision-recall curve (PRC_AUC), and other metrics. The best-performing model was the XGB which had an accuracy of 92.3%, recall of 94.2%, F1-Score of 92.4%, and ROC_AUC of 97.5%. The pairwise Mann–Whitney U-test analysis showed that the second-best model (GB) and the third-best model (RF) did not perform significantly worse than the best model (XGB) and had the following: GB had an accuracy of 91.7%, recall of 94.2%, F1-Score of 91.9%, and ROC_AUC of 97.1%. RF had an accuracy of 90.8%, recall of 93.6%, F1-Score of 91.0%, and ROC_AUC of 96.8%. Other models showed similar results for the same metrics checked. The study successfully derived and validated the selected ML models and predicted mortality effectively with reasonably high performance in the stated metrics. The feature importance analysis found that knowledge of underlying health conditions about patients’ hospital length of stay (LOS), white blood cell count, age, and other factors can help healthcare providers offer lifesaving services on time, improve pandemic preparedness, and decongest health facilities in Zambia and other countries with similar settings

Acceptance of Cervical Cancer Screening and its Correlates Among Women of a Peri-Urban High-Density Residential Area in Ndola, Zambia

Background: Zambia has one of the highest cervical cancer incidence and mortality rates in the world. Cervical cancer screening leads to reduction in the incidence of invasive disease. The objectives of the study were to determine the level of acceptance of cervical cancer screening and its correlates among women of a peri-urban high-density residential area in Ndola, Zambia. Methods: A cross sectional study was conducted. With a population size of 12,000 women in reproductive age and using an expected frequency of 50 + 5% and at 95% confidence interval, the required sample size was 372. A stratified sampling method was used to select participants. Independent factors that were associated with the outcome were established using multi-variate logistic regression. Adjusted odds ratios and their 95% confidence intervals are reported. Results: In total, 355 out of 372 questionnaires were administered, achieving a response rate of 95.4%. Out of 355 participants, 9 (2.5%) had ever been screened for cervical cancer. In bivariate analyses, factors associated with screened were knowledge of body part affected, screening as a prevention tool, whether cervical cancer was curable in its early stages or not, awareness of cervical cancer screening, knowledge on frequency of screening and cervical cancer screening causing harm. However, in multivariate analysis, participants who knew that cervical cancer screening prevented cervical cancer were 3.58 (95% CI [1.49, 8.64]) times more likely to have been screened than those who did not have the knowledge. Participants who knew that cervical cancer is curable were 2.76 (95% CI [1.92, 8.31]) times more likely to have been screened than those who did not have the knowledge. Conclusion and Global Health Implications: The uptake of screening was low. Interventions should be designed to increase uptake of screening for cervical cancer by considering factors that have been identified in the current study that are independently associated with cervical cancer screening among this population. Copyright © 2018 Kabalika et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Evaluating the costs of cholera illness and cost-effectiveness of a single dose oral vaccination campaign in Lusaka, Zambia.

IntroductionIn 2016, for the very first time, the Ministry of Health in Zambia implemented a reactive outbreak response to control the spread of cholera and vaccinated at-risk populations with a single dose of Shancol-an oral cholera vaccine (OCV). This study aimed to assess the costs of cholera illness and determine the cost-effectiveness of the 2016 vaccination campaign.MethodologyFrom April to June 2017, we conducted a retrospective cost and cost-effectiveness analysis in three peri-urban areas of Lusaka. To estimate costs of illness from a household perspective, a systematic random sample of 189 in-patients confirmed with V. cholera were identified from Cholera Treatment Centre registers and interviewed for out-of-pocket costs. Vaccine delivery and health systems costs were extracted from financial records at the District Health Office and health facilities. The cost of cholera treatment was derived by multiplying the subsidized cost of drugs by the quantity administered to patients during hospitalisation. The cost-effectiveness analysis measured incremental cost-effectiveness ratio-cost per case averted, cost per life saved and cost per DALY averted-for a single dose OCV.ResultsThe mean cost per administered vaccine was US$1.72. Treatment costs per hospitalized episode were US$14.49-US$18.03 for patients ≤15 years old and US$17.66-US$35.16 for older patients. Whereas households incurred costs on non-medical items such as communication, beverages, food and transport during illness, a large proportion of medical costs were borne by the health system. Assuming vaccine effectiveness of 88.9$1,500, the costs per case averted were estimated US$369-US$532. Costs per life year saved ranged from US$18,515-US$27,976. The total cost per DALY averted was estimated between US$698-US$1,006 for patients ≤15 years old and US$666-US$1,000 for older patients.ConclusionOur study determined that reactive vaccination campaign with a single dose of Shancol for cholera control in densely populated areas of Lusaka was cost-effective

Euvichol-plus vaccine campaign coverage during the 2017/2018 cholera outbreak in Lusaka district, Zambia: a cross-sectional descriptive study

Objective To determine the coverage for the oral cholera vaccine (OCV) campaign conducted during the 2017/2018 cholera outbreak in Lusaka, Zambia.Study design A descriptive cross-sectional study employing survey method conducted among 1691 respondents from 369 households following the second round of the 2018 OCV campaign.Study setting Four primary healthcare facilities and their catchment areas in Lusaka city (Kanyama, Chawama, Chipata and Matero subdistricts).Participants A total of 1691 respondents 12 months and older sampled from 369 households where the campaign was conducted. A satellite map-based sampling technique was used to randomly select households.Data management and analysis A pretested electronic questionnaire uploaded on an electronic tablet (ODK V.1.12.2) was used for data collection. Descriptive statistics were computed to summarise respondents’ characteristics and OCV coverage per dose. Bivariate analysis (χ2 test) was conducted to stratify OCV coverage according to age and sex for each round (p<0.05).Results The overall coverage for the first, second and two doses were 81.3% (95% CI 79.24% to 83.36%), 72.1% (95% CI 69.58% to 74.62%) and 66% (95% CI 63.22% to 68.78%), respectively. The drop-out rate was 18.8% (95% CI 14.51% to 23.09%). Of the 81.3% who received the first dose, 58.8% were female. Among those who received the second dose, the majority (61.0%) were females aged between 5 and 14 years (42.6%) and 15 and 35 years (27.7%). Only 15.5% of the participants aged between 36 and 65 and 2.5% among those aged above 65 years received the second dose.Conclusion These findings confirm the 2018 OCV campaign coverage and highlight the need for follow-up surveys to validate administrative coverage estimates using population-based methods. Reliance on health facility data alone may mask low coverage and prevent measures to improve programming. Future public health interventions should consider sociodemographic factors in order to achieve optimal vaccine coverage