Background There is a geographic disparity in the epidemiology of HIV infection globally. These differences are interrelated with the sociodemographic and behavioural circumstances applicable to the respective regions. For instance, the HIV-2 strain is mostly found in West Africa. The most significant number of people injecting drugs (PWID) are in East and South-East Asia, North America, and Eastern Europe; they also have the highest prevalence of HIV among PWID. Spatiotemporal analytical methods use geographic and time-related factors to explain observed spatial heterogeneity; thereby, identifying disease patterns, risk factors, and trends relevant to a particular region. Spatiotemporal analytical methods use geographic and time-related factors to explain observed spatial heterogeneity; thereby, identifying disease patterns, risk factors, and trends relevant to a particular region. Objectives This paper presents a protocol for a systematic review that will describe the methods used in the spatial analysis of HIV epidemiology globally. Methods A systematic literature search of geospatial studies of HIV will be conducted using PubMed, EBSCOhost, and Google scholar; with neither language nor date restriction from inception to date. The protocol for this systematic review was prospectively registered in PROSPERO with ID number –CRD42022314604. Results Results will be available once the review is finalised. Discussion This systematic review will identify and report the various spatial analytical methods that have been employed in HIV epidemiology; in addition to highlighting the predominant spatial methodologies applied.

Background COVID-19 has accounted for approximately six million deaths globally. Several risk factors have been identified. However, population profile varies in different population groups. Aim The study aim is to describe the population profile of COVID-19 mortality in Rivers State, Nigeria using captured population-based health records. Study design: Retrospective cohort study Methods Using electronic State Health Records, a secondary data analysis was conducted on recorded COVID-19 mortality. Data were obtained from the Public Health Emergency Operations Centre (PHEOC) at the State Ministry of Health. Data was accessed from the PHEOC database, and it included COVID-19 related mortality. Data were collected on demographics, pre-existing comorbidity, symptoms, facility managed, patient status, treatment outcome, and dates of related events. Cohort characteristics were described using means and proportions. Results There were 191 COVID-19 deaths identified. The mean age was 57.08; of which 144 were male (75.4%). The 51–65-year age group had the highest mortality count (38.9%). Over 50% of the patients were hypertensive and diabetes was the second most common comorbidity (28.8%). Running nose, cough, fever and breathing difficulties were the most reported COVID-19 symptoms. Conclusion Data from this study shows higher mortality in men from COVID-19; and, among cases with hypertension and diabetes. Additionally, age and the presence of comorbidities may be associated with COVID-19 mortality. Future research in this area could further explain these findings.