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Abstract Objectives Visual inspection with acetic acid (VIA) is a low‐cost approach for cervical cancer screening used in most low‐ and middle‐income countries (LMICs) but, similar to other visual tests, is subjective and requires sustained training and quality assurance. We developed, trained, and validated an artificial‐intelligence‐based “Automated Visual Evaluation” (AVE) tool that can be adapted to run on smartphones to assess smartphone‐captured images of the cervix and identify precancerous lesions, helping augment VIA performance. Design Prospective study. Setting Eight public health facilities in Zambia. Participants A total of 8204 women aged 25–55. Interventions Cervical images captured on commonly used low‐cost smartphone models were matched with key clinical information including human immunodeficiency virus (HIV) and human papillomavirus (HPV) status, plus histopathology analysis (where applicable), to develop and train an AVE algorithm and evaluate its performance for use as a primary screen and triage test for women who are HPV positive. Main Outcome Measures Area under the receiver operating curve (AUC); sensitivity; specificity. Results As a general population screening tool for cervical precancerous lesions, AVE identified cases of cervical precancerous and cancerous (CIN2+) lesions with high performance (AUC = 0.91, 95% confidence interval [CI] = 0.89–0.93), which translates to a sensitivity of 85% (95% CI = 81%–90%) and specificity of 86% (95% CI = 84%–88%) based on maximizing the Youden's index. This represents a considerable improvement over naked eye VIA, which as per a meta‐analysis by the World Health Organization (WHO) has a sensitivity of 66% and specificity of 87%. For women living with HIV, the AUC of AVE was 0.91 (95% CI = 0.88–0.93), and among those testing positive for high‐risk HPV types, the AUC was 0.87 (95% CI = 0.83–0.91). Conclusions These results demonstrate the feasibility of utilizing AVE on images captured using a commonly available smartphone by nurses in a screening program, and support our ongoing efforts for moving to more broadly evaluate AVE for its clinical sensitivity, specificity, feasibility, and acceptability across a wider range of settings. Limitations of this study include potential inflation of performance estimates due to verification bias (as biopsies were only obtained from participants with visible aceto‐white cervical lesions) and due to this being an internal validation (the test data, while independent from that used to develop the algorithm was drawn from the same study).

Abstract Background WHO has recommended HPV testing for cervical screening where it is practical and affordable. If used, it is important to both clarify and implement the clinical management of positive results. We estimated the performance in Lusaka, Zambia of a novel screening/triage approach combining HPV typing with visual assessment assisted by a deep-learning approach called automated visual evaluation (AVE). Methods In this well-established cervical cancer screening program nested inside public sector primary care health facilities, experienced nurses examined women with high-quality digital cameras; the magnified illuminated images permit inspection of the surface morphology of the cervix and expert telemedicine quality assurance. Emphasizing sensitive criteria to avoid missing precancer/cancer, ~ 25% of women screen positive, reflecting partly the high HIV prevalence. Visual screen-positive women are treated in the same visit by trained nurses using either ablation (~ 60%) or LLETZ excision, or referred for LLETZ or more extensive surgery as needed. We added research elements (which did not influence clinical care) including collection of HPV specimens for testing and typing with BD Onclarity™ with a five channel output (HPV16, HPV18/45, HPV31/33/52/58, HPV35/39/51/56/59/66/68, human DNA control), and collection of triplicate cervical images with a Samsung Galaxy J8 smartphone camera™ that were analyzed using AVE, an AI-based algorithm pre-trained on a large NCI cervical image archive. The four HPV groups and three AVE classes were crossed to create a 12-level risk scale, ranking participants in order of predicted risk of precancer. We evaluated the risk scale and assessed how well it predicted the observed diagnosis of precancer/cancer. Results HPV type, AVE classification, and the 12-level risk scale all were strongly associated with degree of histologic outcome. The AVE classification showed good reproducibility between replicates, and added finer predictive accuracy to each HPV type group. Women living with HIV had higher prevalence of precancer/cancer; the HPV-AVE risk categories strongly predicted diagnostic findings in these women as well. Conclusions These results support the theoretical efficacy of HPV-AVE-based risk estimation for cervical screening. If HPV testing can be made affordable, cost-effective and point of care, this risk-based approach could be one management option for HPV-positive women.

ABSTRACT: Objectives: Tuberculosis remains a global emergency. In Zambia only 55% of tuberculosis cases are diagnosed. We performed a study to determine incidental cases of tuberculosis seen at forensic autopsy of individuals who died suddenly and unexpectedly in the community in Lusaka, Zambia. Methods: Whole-body autopsies were performed according to Standard Operating Procedures. Representative samples obtained from relevant organs were subjected to pathological examination. Information on circumstances surrounding the death was obtained. Data on patient demographics, gross and microscopic pathological findings, and cause(s) of death were analysed. Results: Incidental tuberculosis was found in 52 cases (45 male, 7 female, age range 14-66) out of 4286 whole-body autopsies. 41/52 (80%) were aged 21-50 years. One was a 14-year old boy who died during a football match. 39/52 (75%) deaths were attributable specifically to tuberculosis only. Other deaths were due to acute alcohol intoxication(4), violence(7), ruptured ectopic pregnancy(1), bacterial meningitis (1). All the cases were from poor socio-economic backgrounds and lived in high-density areas of Lusaka. Conclusions: Incidental cases of active tuberculosis undiagnosed antemortem seen at forensic autopsy reflects major gaps in the national TB control programs. More investments into proactive screening, testing, treatment activities, and accurate data collection are required.

ABSTRACT: Background: Data from Africa regarding sudden and unexpected COVID-19 community deaths and underlying pathological, demographic, and co-morbidity features require definition. Methods: We performed a case series of COVID-19-related deaths seen at Forensic Post-Mortem examination of sudden and unexpected Community Deaths in Lusaka, Zambia, Africa. Whole-body Post-Mortem examinations were performed according to Standard Operating Procedures. Patient demographics, history, co-morbidities, pathological gross and microscopic findings, and cause(s) of death were recorded. Variables were grouped as frequencies and percentages. Comparison of data was made with autopsy findings of hospital COVID-19 deaths. Findings: Of 21 COVID-19 decedents, 14/21 (66.7%) were male; 18/21, (85.7%) were below 55 years of age (mean age, 40 ± 12.3; range, 20-73). The median duration of symptoms was 1 day (range 0-2); 9/21 (42.9%) had co-morbidities, with hypertension and obesity being the most common. Main post-mortem findings were diffuse alveolar damage (DAD) (80.9%), saddle and shower emboli (38.1%, respectively), and pneumonia (14.3%). Pulmonary thromboembolism (76.2%), DAD (14.3%), and SARS-CoV-2 pneumonia (9.5%) were common causes of death. Conclusions: COVID-19 is an important cause of death to consider in forensic investigations of sudden and unexpected community deaths. Risk factors for the younger age of COVID-19 deaths and thromboembolism need to be identified.

Background: Since information on the pathology of COVID-19 from sub-Saharan Africa (SSA) remains scarce, the objective of our study was to define the gross pathology and histological features of COVID-19. We report data from 29 whole-body autopsies of COVID-19 deaths occurring in hospitals in Lusaka, Zambia - the first large autopsy case series from Africa. Methods: We performed a descriptive post-mortem examination study of inpatient COVID-19 related deaths at two hospitals in Lusaka, Zambia. Whole-body autopsies were conducted according to Standard Operating Procedures. Gross and histopathological examinations of all organs were performed. Patient demographics, history, co-morbidities, autopsy gross and microscopic findings, and cause(s) of death were recorded and analyzed using STATA version 14. Variables were grouped and presented as frequencies and percentages. Findings: Autopsies were performed on 29 decedents (mean age = 44 ± 15.8years; age range = 19-82; 17/29 [58.8%] males). 22/29 [75.9%] cases were

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.