Cooking with dirty-burning fuels is associated with health risk from household air pollution. We assessed the prevalence of and factors associated with the use of cooking fuels, and attitudes and barriers towards use of liquefied petroleum gas (LPG). This was a cross-sectional, population-based survey conducted in 519 households in Lagos, Nigeria. We used a structured questionnaire to obtain information regarding choice of household cooking fuel and the attitudes towards the use of LPG. Kerosene was the most frequently used cooking fuel (n = 475, 91.5%; primary use n = 364, 70.1%) followed by charcoal (n = 159, 30.6%; primary use n = 88, 17%) and LPG (n = 86, 16.6%; primary use n = 63, 12.1%). Higher level of education, higher income and younger age were associated with LPG vs. kerosene use. Fuel expenditure on LPG was significantly lower than for kerosene ( $\sout{\mathrm{N}}$ (Naira) 2169.0 ± 1507.0 vs. $\sout{\mathrm{N}}$ 2581.6 ± 1407.5). Over 90% of non-LPG users were willing to switch to LPG but cited safety issues and high cost as potential barriers to switching. Our findings suggest that misinformation and beliefs regarding benefits, safety and cost of LPG are important barriers to LPG use. An educational intervention program could be a cost-effective approach to improve LPG adoption and should be formally addressed through a well-designed community-based intervention study.

Access to quality hypertension care is often poor in sub-Saharan Africa. Some community pharmacies offer hypertension monitoring services, with and without involvement of medical doctors. To directly connect pharmacy staff and cardiologists a care model including a mobile application (mHealth) for remote patient monitoring was implemented and pilot tested in Lagos, Nigeria. Pharmacists provided blood pressure measurements and counselling. Cardiologists enrolled patients in the pilot program and remotely monitored them, for which patients paid a monthly fee. We evaluated the feasibility of this care model at five private community pharmacies. Outcome measures were retention in care, blood pressure change, quality of care, and patients’ and healthcare providers’ satisfaction with the care model. Patients participated in the care model’s pilot at one of the five pharmacies for approximately 6–8 months from February 2016. We conducted structured patient interviews and blood pressure measurements at pilot entry and exit, and used exports of the mHealth-application, in-depth interviews and focus group discussions with patients, pharmacists and cardiologists. Of 336 enrolled patients, 236 (72%) were interviewed at pilot entry and exit. According to the mHealth data 71% returned to the pharmacy after enrollment, with 3.3 months (IQR: 2.2–5.4) median duration of activity in the mHealth-application. Patients self-reported more visits than recorded in the mHealth data. Pharmacists mentioned use of paper records, understaffing, the application not being user-friendly, and patients’ unwillingness to pay as reasons for underreporting. Mean systolic blood pressure decreased 9.9 mmHg (SD: 18). Blood pressure on target increased from 24 to 56% and an additional 10% had an improved blood pressure at endline, however this was not associated with duration of mHealth activity. Patients were satisfied because of accessibility, attention, adherence and information provision. Patients, pharmacists and cardiologists adopted the care model, albeit with gaps in mHealth data. Most patients were satisfied, and their mean blood pressure significantly reduced. Usage of the mHealth application, pharmacy incentives, and a modified financing model are opportunities for improvement. In addition, costs of implementation and availability of involved healthcare providers need to be investigated before such a care model can be further implemented.

The objective of this study was to describe the epidemiology of COVID-19 in Nigeria with a view of generating evidence to enhance planning and response strategies. A national surveillance dataset between 27 February and 6 June 2020 was retrospectively analysed, with confirmatory testing for COVID-19 done by real-time polymerase chain reaction (RT-PCR). The primary outcomes were cumulative incidence (CI) and case fatality (CF). A total of 40 926 persons (67% of total 60 839) had complete records of RT-PCR test across 35 states and the Federal Capital Territory, 12 289 (30.0%) of whom were confirmed COVID-19 cases. Of those confirmed cases, 3467 (28.2%) had complete records of clinical outcome (alive or dead), 342 (9.9%) of which died. The overall CI and CF were 5.6 per 100 000 population and 2.8%, respectively. The highest proportion of COVID-19 cases and deaths were recorded in persons aged 31–40 years (25.5%) and 61–70 years (26.6%), respectively; and males accounted for a higher proportion of confirmed cases (65.8%) and deaths (79.0%). Sixty-six per cent of confirmed COVID-19 cases were asymptomatic at diagnosis. In conclusion, this paper has provided an insight into the early epidemiology of COVID-19 in Nigeria, which could be useful for contextualising public health planning.

Background With reports of surges in COVID-19 case numbers across over 50 countries, country-level epidemiological analysis is required to inform context-appropriate response strategies for containment and mitigation of the outbreak. We aimed to compare the epidemiological features of the first and second waves of COVID-19 in Nigeria. Methods We conducted a retrospective analysis of the Surveillance Outbreak Response Management and Analysis System data of the first and second epidemiological waves, which were between 27 February and 24 October 2020, and 25 October 2020 to 3 April 2021, respectively. Descriptive statistical measures including frequencies and percentages, test positivity rate (TPR), cumulative incidence (CI) and case fatality rates (CFRs) were compared. A p value of <0.05 was considered statistically significant. All statistical analyses were carried out in STATA V.13. Results There were 802 143 tests recorded during the study period (362 550 and 439 593 in the first and second waves, respectively). Of these, 66 121 (18.2%) and 91 644 (20.8%) tested positive in the first and second waves, respectively. There was a 21.3% increase in the number of tests conducted in the second wave with TPR increasing by 14.3%. CI during the first and second waves were 30.3/100 000 and 42.0/100 000 respectively. During the second wave, confirmed COVID-19 cases increased among females and people 30 years old or younger and decreased among urban residents and individuals with travel history within 14 days of sample collection (p value <0.001). Most confirmed cases were asymptomatic at diagnosis during both waves: 74.9% in the first wave; 79.7% in the second wave. CFR decreased during the second wave (0.7%) compared with the first wave (1.8%). Conclusion Nigeria experienced a larger but less severe second wave of COVID-19. Continued implementation of public health and social measures is needed to mitigate the resurgence of another wave.

Background: In sub-Saharan Africa, cardiovascular disease is becoming a leading cause of death, with high blood pressure as number one risk factor. In Nigeria, access and adherence to hypertension care are poor. A pharmacy-based hypertension care model with remote monitoring by cardiologists through mHealth was piloted in Lagos to increase accessibility to quality care for hypertensive patients. Objectives: To describe patients’ and healthcare providers’ perceptions and practices regarding hypertension, pharmacy-based care, and mHealth and explore how this information may improve innovative hypertension service delivery. Methods: This study consisted of observations of patient–pharmacy staff interactions and hypertension care provided, four focus group discussions and in-depth interviews with 30 hypertensive patients, nine community pharmacists, and six cardiologists, and structured interviews with 328 patients. Results: Most patients were knowledgeable about biomedical causes and treatment of hypertension, but often ignorant about the silent character of hypertension. Reasons mentioned for not adhering to treatment were side effects, financial constraints, lack of health insurance, and cultural or religious reasons. Pharmacists additionally mentioned competition with informal, cheaper healthcare providers. Patients highly favored pharmacy-based care, because of the pharmacist–patient relationship, accessibility, small-scale, and a pharmacy's registration at an association. The majority of respondents were positive towards mHealth. Conclusion: Facilitating factors for innovative pharmacy-based hypertension care were: patients’ biomedical perceptions, pharmacies’ strong position in the community, and respondents’ positive attitude towards mHealth. We recommend health education and strengthening pharmacists’ role to address barriers, such as misperceptions that hypertension always is symptomatic, treatment nonadherence, and unfamiliarity with mHealth. Future collaboration with insurance providers or other financing mechanisms may help diminish patients’ financial barriers to appropriate hypertension treatment.