Assessment of antimicrobial resistance laboratory-based surveillance capacity of hospitals in Zambia: findings and implications for system strengthening

BACKGROUND

A well-established antimicrobial resistance (AMR) laboratory-based surveillance (LBS) is of utmost importance in a country like Zambia which bears a significant proportion of the world's communicable disease burden. This study assessed the capacity of laboratories in selected hospitals to conduct AMR surveillance in Zambia.

METHODS

This cross-sectional exploratory study was conducted among eight purposively selected hospitals in Zambia between August 2023 and December 2023. Data were collected using the self-scoring Laboratory Assessment of Antibiotic Resistance Testing Capacity (LAARC) tool.

FINDINGS

Of the assessed facilities, none had full capacity to conduct AMR surveillance with varying capacities ranging from moderate (63% (5/8)) to low (38% (3/8)). Some of the barriers of AMR-LBS were the lack of an electronic laboratory information system (63% (5/8)) and the lack of locally generated antibiograms (75% (6/8)). Quality control for antimicrobial susceptibility testing (AST), pathogen identification and media preparation had the lowest overall score among all of the facilities with a score of 14%, 20% and 44%, respectively. The highest overall scores were in specimen processing (79%), data management (78%), specimen collection, transport and management (71%), and safety (70%). Most facilities had standard operating procedures in place but lacked specimen-specific standard operating procedures.

CONCLUSION

The absence of laboratories with full capacity to conduct AMR surveillance hinders efforts to combat AMR and further complicates the treatment outcomes of infectious diseases. Establishing and strengthening LBS systems are essential in quantifying the burden of AMR and supporting the development of local antibiograms and treatment guidelines.

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.

Spatial factors for COVID-19 associated community deaths in an urban area of Lusaka, Zambia: an observational study

We retrospectively analyzed spatial factors for coronavirus disease 2019 (COVID-19)-associated community deaths i.e., brought-in-dead (BID) in Lusaka, Zambia, between March and July 2020. A total of 127 cases of BID with geocoordinate data of their houses were identified during the study period. Median interquartile range (IQR) of the age of these cases was 49 (34-70) years old, and 47 cases (37.0%) were elderly individuals over 60 years old. Seventy-five cases (75%) of BID were identified in July 2020, when the total number of cases and deaths was largest in Zambia. Among those whose information regarding their underlying medical condition was available, hypertension was most common (22.9%, 8/35). Among Lusaka's 94 townships, the numbers (median, IQR) of cases were significantly larger in those characterized as unplanned residential areas compared to planned areas (1.0, 0.0-4.0 vs 0.0, 0.0-1.0; p=0.030). The proportion of individuals who require more than 30 minutes to obtain water was correlated with a larger number of BID cases per 105 population in each township (rho=0.28, p=0.006). The number of BID cases was larger in unplanned residential areas, which highlighted the importance of targeted public health interventions specifically to those areas to reduce the total number of COVID-19 associated community deaths in Lusaka. Brought-in-dead surveillance might be beneficial in monitoring epidemic conditions of COVID-19 in such high-risk areas. Furthermore, inadequate access to water, sanitation, and hygiene (WASH) might be associated with such distinct geographical distributions of COVID-19 associated community deaths in Lusaka, Zambia.

An evaluation of the Zambia influenza sentinel surveillance system, 2011-2017

Background

Over the past decade, influenza surveillance has been established in several African countries including Zambia. However, information on the on data quality and reliability of established influenza surveillance systems in Africa are limited. Such information would enable countries to assess the performance of their surveillance systems, identify shortfalls for improvement and provide evidence of data reliability for policy making and public health interventions.

Methods

We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza surveillance system (ISS) in Zambia during 2011–2017 using 9 attributes: (i) data quality and completeness, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability, (viii) utility, and (ix) sustainability. Each attribute was evaluated using pre-defined indicators. For each indicator we obtained the proportion (expressed as percentage) of the outcome of interest over the total. A scale from 1 to 3 was used to provide a score for each attribute as follows: < 60% (as obtained in the calculation above) scored 1 (weak performance); 60–79% scored 2 (moderate performance); ≥80% scored 3 (good performance). An overall score for each attribute and the ISS was obtained by averaging the scores of all evaluated attributes.

Results

The overall mean score for the ISS in Zambia was 2.6. Key strengths of the system were the quality of data generated (score: 2.9), its flexibility (score: 3.0) especially to monitor viral pathogens other than influenza viruses, its simplicity (score: 2.8), acceptability (score: 3.0) and stability (score: 2.6) over the review period and its relatively low cost ($310,000 per annum). Identified weaknesses related mainly to geographic representativeness (score: 2.0), timeliness (score: 2.5), especially in shipment of samples from remote sites, and sustainability (score: 1.0) in the absence of external funds.

Conclusions

The system performed moderately well in our evaluation. Key improvements would include improvements in the timeliness of samples shipments and geographical coverage. However, these improvements would result in increased cost and logistical complexity. The ISSS in Zambia is largely reliant on external funds and the acceptability of maintaining the surveillance system through national funds would require evaluation.

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

INTRODUCTION

In 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.

METHODOLOGY

From 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.

RESULTS

The 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% and 63%, a life expectancy of 62 years and Gross Domestic Product (GDP) per capita of US$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.

CONCLUSION

Our study determined that reactive vaccination campaign with a single dose of Shancol for cholera control in densely populated areas of Lusaka was cost-effective.

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.

Prevalence and Correlates for Psychosocial Distress Among In-School Adolescents in Zambia

There is scanty information on correlates for psychosocial distress in Zambia. Secondary analysis was conducted using the data collected in 2004 in Zambia during the global school-based health survey to determine the prevalence and correlates for psychosocial distress. Logistic regression analyses were used to estimate magnitudes of associations between exposure factors and the outcome, while the Yates' corrected Chi-squared test was used to compare proportions at the 5% significance level. A total of 2257 students participated in the survey of which 54.2% were males. Males were generally older than females (p < 0.001). Significantly, more females than males were bullied (p = 0.036), involved in a fight (p = 0.019), and consumed alcohol (p = 0.012). Psychosocial distress was detected in 15.7% of the participants (14.4% of males and 16.8% of females). Age <14 years, male gender, parental support for males, and having close friends were protective factors against psychosocial distress. Risk factors for psychosocial distress were being bullied, involvement in a fight, alcohol consumption, being physically active, and parental support. The prevalence of psychosocial distress among adolescents in Zambia appears to be common. There is a need to validate the psychosocial distress indicators that were used in the current study.