Trends and Inequalities in Maternal and Newborn Health Services for Unplanned Settlements of Lusaka City, Zambia.

Living conditions and other factors in urban unplanned settlements present unique challenges for improving maternal and newborn health (MNH), yet MNH inequalities associated with such challenges are not well understood. This study examined trends and inequalities in coverage of MNH services in the last 20 years in unplanned and planned settlements of Lusaka City, Zambia. Geospatial information was used to map Lusaka's settlements and health facilities. Zambia Demographic Health Surveys (ZDHS 2001, 2007, 2013/2014, and 2018) were used to compare antenatal care (ANC), institutional delivery, and Cesarean section (C-section) coverage, and neonatal mortality rates between the poorer 60% and richer 40% households. Health Management Information System (HMIS) data from 2018 to 2021 were used to compute service volumes and coverage rates for ANC1 and ANC4, and institutional delivery and C-sections by facility level and type in planned and unplanned settlements. Although the correlation is not exact, our data analysis showed close alignment; and thus, we opted to use the 60% poorer and 40% richer groups as a proxy for households in unplanned versus planned settlements. Unplanned settlements were serviced by primary centers or first-level hospitals. ZDHS findings show that by 2018, at least one ANC visit and institutional delivery became nearly universal throughout Lusaka, but early and four or more ANC visits, C-sections, and neonatal mortality rates remained worse among poorer than richer women in ZDHS. In HMIS, ANC and institutional delivery volumes were highest in public facilities, especially in unplanned settlements. The volume of C-sections was much greater within facilities in planned than unplanned settlements. Our study exposed persistent gaps in timing and use of ANC and emergency obstetric care between unplanned and planned communities. Closing such gaps requires strengthening outreach early and consistently in pregnancy and increasing emergency obstetric care capacities and referrals to improve access to important MNH services for women and newborns in Lusaka's unplanned settlements.

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.

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.

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.

First COVID-19 case in Zambia - Comparative phylogenomic analyses of SARS-CoV-2 detected in African countries.

Since its first discovery in December 2019 in Wuhan, China, COVID-19, caused by the novel coronavirus SARS-CoV-2, has spread rapidly worldwide. While African countries were relatively spared initially, the initial low incidence of COVID-19 cases was not sustained for long due to continuing travel links between China, Europe and Africa. In preparation, Zambia had applied a multisectoral national epidemic disease surveillance and response system resulting in the identification of the first case within 48 h of the individual entering the country by air travel from a trip to France. Contact tracing showed that SARS-CoV-2 infection was contained within the patient's household, with no further spread to attending health care workers or community members. Phylogenomic analysis of the patient's SARS-CoV-2 strain showed that it belonged to lineage B.1.1., sharing the last common ancestor with SARS-CoV-2 strains recovered from South Africa. At the African continental level, our analysis showed that B.1 and B.1.1 lineages appear to be predominant in Africa. Whole genome sequence analysis should be part of all surveillance and case detection activities in order to monitor the origin and evolution of SARS-CoV-2 lineages across Africa.

First 100 Persons with COVID-19 - Zambia, March 18-April 28, 2020.

Zambia is a landlocked, lower-middle income country in southern Africa, with a population of 17 million (1). The first known cases of coronavirus disease 2019 (COVID-19) in Zambia occurred in a married couple who had traveled to France and were subject to port-of-entry surveillance and subsequent remote monitoring of travelers with a history of international travel for 14 days after arrival. They were identified as having suspected cases on March 18, 2020, and tested for COVID-19 after developing respiratory symptoms during the 14-day monitoring period. In March 2020, the Zambia National Public Health Institute (ZNPHI) defined a suspected case of COVID-19 as 1) an acute respiratory illness in a person with a history of international travel during the 14 days preceding symptom onset; or 2) acute respiratory illness in a person with a history of contact with a person with laboratory-confirmed COVID-19 in the 14 days preceding symptom onset; or 3) severe acute respiratory illness requiring hospitalization; or 4) being a household or close contact of a patient with laboratory-confirmed COVID-19. This definition was adapted from World Health Organization (WHO) interim guidance issued March 20, 2020, on global surveillance for COVID-19 (2) to also include asymptomatic contacts of persons with confirmed COVID-19. Persons with suspected COVID-19 were identified through various mechanisms, including port-of-entry surveillance, contact tracing, health care worker (HCW) testing, facility-based inpatient screening, community-based screening, and calls from the public into a national hotline administered by the Disaster Management and Mitigation Unit and ZNPHI. Port-of-entry surveillance included an arrival screen consisting of a temperature scan, report of symptoms during the preceding 14 days, and collection of a history of travel and contact with persons with confirmed COVID-19 in the 14 days before arrival in Zambia, followed by daily remote telephone monitoring for 14 days. Travelers were tested for SARS-CoV-2, the virus that causes COVID-19, if they were symptomatic upon arrival or developed symptoms during the 14-day monitoring period. Persons with suspected COVID-19 were tested as soon as possible after evaluation for respiratory symptoms or within 7 days of last known exposure (i.e., travel or contact with a confirmed case). All COVID-19 diagnoses were confirmed using real-time reverse transcription-polymerase chain reaction (RT-PCR) testing (SARS-CoV-2 Nucleic Acid Detection Kit, Maccura) of nasopharyngeal specimens; all patients with confirmed COVID-19 were admitted into institutional isolation at the time of laboratory confirmation, which was generally within 36 hours. COVID-19 patients were deemed recovered and released from isolation after two consecutive PCR-negative test results ≥24 hours apart. A Ministry of Health memorandum was released on April 13, 2020, mandating testing in public facilities of 1) all persons admitted to medical and pediatric wards regardless of symptoms; 2) all patients being admitted to surgical and obstetric wards, regardless of symptoms; 3) any outpatient with fever, cough, or shortness of breath; and 4) any facility or community death in a person with respiratory symptoms, and 5) biweekly screening of all HCWs in isolation centers and health facilities where persons with COVID-19 had been evaluated. This report describes the first 100 COVID-19 cases reported in Zambia, during March 18-April 28, 2020.

Cholera Epidemic - Lusaka, Zambia, October 2017-May 2018.

On October 6, 2017, an outbreak of cholera was declared in Zambia after laboratory confirmation of Vibrio cholerae O1, biotype El Tor, serotype Ogawa, from stool specimens from two patients with acute watery diarrhea. The two patients had gone to a clinic in Lusaka, the capital city, on October 4. Cholera cases increased rapidly, from several hundred cases in early December 2017 to approximately 2,000 by early January 2018 (Figure). In collaboration with partners, the Zambia Ministry of Health (MoH) launched a multifaceted public health response that included increased chlorination of the Lusaka municipal water supply, provision of emergency water supplies, water quality monitoring and testing, enhanced surveillance, epidemiologic investigations, a cholera vaccination campaign, aggressive case management and health care worker training, and laboratory testing of clinical samples. In late December 2017, a number of water-related preventive actions were initiated, including increasing chlorine levels throughout the city's water distribution system and placing emergency tanks of chlorinated water in the most affected neighborhoods; cholera cases declined sharply in January 2018. During January 10-February 14, 2018, approximately 2 million doses of oral cholera vaccine were administered to Lusaka residents aged ≥1 year. However, in mid-March, heavy flooding and widespread water shortages occurred, leading to a resurgence of cholera. As of May 12, 2018, the outbreak had affected seven of the 10 provinces in Zambia, with 5,905 suspected cases and a case fatality rate (CFR) of 1.9%. Among the suspected cases, 5,414 (91.7%), including 98 deaths (CFR = 1.8%), occurred in Lusaka residents.