A population-based estimation of maternal mortality in Lagos State, Nigeria using the indirect sisterhood method.

BACKGROUND: Pregnancy and delivery deaths represent a risk to women, particularly those living in low- and middle-income countries (LMICs). This population-based survey was conducted to provide estimates of the maternal mortality ratio (MMR) in Lagos Nigeria. METHODS: A community-based, cross-sectional study was conducted in mapped Wards and Enumeration Areas (EA) of all Local Government Areas (LGAs) in Lagos, among 9,986 women of reproductive age (15-49 years) from April to August 2022 using a 2-stage cluster sampling technique. A semi-structured, pre-tested questionnaire adapted from nationally representative surveys was administered using REDCap by trained field assistants for data collection on socio-demographics, reproductive health, fertility, and maternal mortality. Data were analysed using SPSS and MMR was estimated using the indirect sisterhood method. Ethical approval was obtained from the Lagos State University Teaching Hospital Health Research and Ethics Committee. RESULTS: Most of the respondents (28.7%) were aged 25-29 years. Out of 546 deceased sisters reported, 120 (22%) died from maternal causes. Sisters of the deceased aged 20-24 reported almost half of the deaths (46.7%) as due to maternal causes, while those aged 45-49 reported the highest number of deceased sisters who died from other causes (90.2%). The total fertility rate (TFR) was calculated as 3.807, the Lifetime Risk (LTR) of maternal death was 0.0196 or 1-in-51, and the MMR was 430 per 100,000 [95% CI: 360-510]. CONCLUSION: Our findings show that the maternal mortality rate for Lagos remains unacceptable and has not changed significantly over time in actual terms. There is need to develop and intensify community-based intervention strategies, programs for private hospitals, monitor MMR trends, identify and contextually address barriers at all levels of maternal care.

Application of the UNAIDS Incidence Patterns Model to Determine the Distribution of New HIV Infection in Lagos State, Nigeria.

BACKGROUND: Identifying patterns in the distribution of new HIV infections in the population is critical for HIV programmatic interventions. This study aimed to determine the distribution of New HIV infection by applying the incidence patterns mathematical model to data from Lagos state. METHODS: The incidence patterns model (IPM) software is a mathematical model developed by UNAIDS to estimate the demographic and epidemic patterns of HIV infections. This model was adapted in Lagos state to predict the distribution of new HIV infections among specified risk groups in the next 12 months. RESULTS: The IPM predicted a total HIV incidence of 37 cases per 100 000 individuals (3979 new infections) will occur among the 15 to 49 subpopulations. The results also showed that sero-concordant HIV-negative couples with external partners (29%), female sex workers (26%), men-having-sex-with-men (18%), and previously married females (6%) accounted for the majority of the estimated new HIV infections. Overall, key populations constitute almost half (48%) of the estimated number of new HIV infections. CONCLUSION: The study helped to identify the population groups contributing significantly to new HIV infections. Therefore, priority interventions should be focused on these groups.

Distribution of Cancer and Cancer Screening and Treatment Services in Lagos: A 10-Year Review of Hospital Records.

PURPOSE: In Lagos State, Nigeria, the population distribution of cancers is poorly described because studies are conducted at a few tertiary hospitals. Therefore, this study aims to map all health facilities where cancer screening takes place and describe the cases of cancer screened for and treated. METHODS: A cross-sectional survey to identify facilities involved in screening and management of cancers was performed followed by extraction of data on individual cases of cancer screened for and treated at these facilities from 2011 to 2020. All health care facilities in the state were visited, and the survey was performed using standardized national tools modified to capture additional information on cancer screening and treatment. Data analysis was performed using STATA version 14 and R version 3.6.3. RESULTS: Cervical cancer was the commonest cancer, accounting for 55% of 2,420 cancers screened, followed by breast (41%), prostate (4%), and colorectal cancers (0.2%). Of the 7,682 cancers treated among Lagos residents, the top five were breast (45%), colorectal (8%), cervical (8%), prostate (5%), and ovarian (4%). The female:male ratio of cancer cases was 3:1. The peak age for cancer among females and males was in the 40- to 49-year age group and 60- to 69-year age group, respectively. The Ikorodu local government area had the highest rate of reported cancer per million population. CONCLUSION: Cancer screening is poor with a significant gap in screening for breast cancer since it is the commonest cancer in the state. The findings indicate the urgent need for the establishment of organized screening programs for the predominant cancers in the state and the prioritization of cancer research that addresses key policy and program questions.

'Long COVID': persistent COVID-19 symptoms in survivors managed in Lagos State, Nigeria.

BACKGROUND: Coronavirus disease once thought to be a respiratory infection is now recognised as a multi-system disease affecting the respiratory, cardiovascular, gastrointestinal, neurological, immune, and hematopoietic systems. An emerging body of evidence suggests the persistence of COVID-19 symptoms of varying patterns among some survivors. This study aimed to describe persistent symptoms in COVID-19 survivors and investigate possible risk factors for these persistent symptoms. METHODS: The study used a retrospective study design. The study population comprised of discharged COVID-19 patients. Demographic information, days since discharge, comorbidities, and persistent COVID-19 like symptoms were assessed in patients attending the COVID-19 outpatient clinic in Lagos State. Statistical analysis was done using STATA 15.0 software (StataCorp Texas) with significance placed at p-value < 0.05. RESULTS: A total of 274 patients were enrolled in the study. A majority were within the age group > 35 to ≤49 years (38.3%), and male (66.1%). More than one-third (40.9%) had persistent COVID-19 symptoms after discharge, and 19.7% had more than three persistent COVID-like symptoms. The most persistent COVID-like symptoms experienced were easy fatigability (12.8%), headaches (12.8%), and chest pain (9.8%). Symptomatic COVID-19 disease with moderate severity compared to mild severity was a predictor of persistent COVID-like symptoms after discharge (p < 0.05). CONCLUSION: Findings from this study suggests that patients who recovered from COVID-19 disease may still experience COVID-19 like symptoms, particularly fatigue and headaches. Therefore, careful monitoring should be in place after discharge to help mitigate the effects of these symptoms and improve the quality of life of COVID-19 survivors.

Clinical characteristics, predictors of symptomatic coronavirus disease 2019 and duration of hospitalisation in a cohort of 632 Patients in Lagos State, Nigeria.

OBJECTIVE: The clinical spectrum of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still evolving. This study describes the clinical characteristics and investigates factors that predict symptomatic presentation and duration of hospitalisation in a cohort of coronavirus disease 2019 (COVID-19) patients managed in Lagos, Nigeria. METHODOLOGY: This was a retrospective assessment of patients hospitalised with COVID-19 disease in six dedicated facilities in Lagos, Nigeria, between April 1st and May 31st 2020. Participants were individuals with laboratory-confirmed SARS-CoV-2 infection. The outcome measures were presence of symptoms and duration of hospitalisation. Demographic and comorbidity data were also obtained. Statistical analysis was done using STATA 15.0 software, with P < 0.05 being considered statistically significant. RESULTS: A total of 632 cases were analysed. The median age was 40 years (IQR: 30.5-49); male patients accounted for 60.1%. About 63% of patients were asymptomatic at presentation. Among the symptomatic, the most common symptoms were cough (47.4%) and fever (39.7%). The most common comorbidities were hypertension (16.8%) and diabetes (5.2%). The median duration of hospitalisation was 10 days (IQR: 8-14). Comorbidities increased the odds of presenting with symptoms 1.6-fold (P = 0.025) for one comorbidity and 3.2-fold (P = 0.005) for ≥2 comorbidities. Individuals aged ≥50 years were twice as likely to be hospitalised for more than 14 days compared to individuals aged <50 years (P = 0.016). CONCLUSION: Most individuals had no symptoms with comorbidities increasing the likelihood of symptoms. Older age was associated with longer duration of hospitalisation. Age and comorbidities should be used for COVID-19 triaging for efficient resource allocation.