The paper employed recent time series econometrics to analyze and determine relationships between capital account liberalization and economic growth in the West African Monetary Zone 2 (WAMZ) for the period 1980-2012. For the purpose of clearly ascertaining the impact of the variables of interest on economic growth, a country by country estimation was carried out. The short-run and long-run relationships between capital account openness and economic growth were investigated by applying the autoregressive distributive lag (ARDL) bounds testing approach suggested by Pesaran et al. (2001). The empirical results of the ARDL models showed a significant positive relationship between capital account liberalization and growth in Ghana and Sierra Leone. This suggests that the removal of restrictions on capital accounts in Ghana and Sierra Leone would promote economic growth in these countries in the long-run. Liberalization had positive and significant impact on growth in Ghana even in the short-run. However, there was no significant long-run relationship between liberalization and growth in The Gambia, Guinea, Liberia and Nigeria, implying that opening of the capital account should be gradual and complemented with sound macroeconomic and financial policy. Overall, the diagnostic tests indicated that our ARDL models were stable.

Key populations (KPs) are particularly vulnerable to HIV infection and efforts to prevent HIV infections among KPs have been less successful, largely due to existing laws and legislation that classify the groups as illegal. Understanding the HIV infection pathway and the burden of HIV infection among Female Sex Workers (FSWs), Transgender people (TG), Men who have sex with Men (MSM), People who Inject Drugs (PWID), and Prison Inmates (PIs) is critical to combatting the HIV epidemic globally. This study aims to estimate HIV prevalence and model the risk factors of HIV positivity rate among the aforementioned KPs in Sierra Leone. This study used Time Location Sampling, Respondent Driven Sampling (RDS), and Conventional cluster Sampling designs to generate a representative sample of FSWs, MSM, TG, PI, and PWID. HIV prevalence and the corresponding 95% confidence intervals among each KP were estimated by adjusting for sampling weight using the logit-transformed confidence intervals. To determine correlates of HIV test positivity among KPs, a multivariable modified Poisson regression model that adjusts for RDS survey weights was used and sensitivity analysis was conducted using a multivariable logistic regression model with cluster robust standard errors. The prevalence of HIV among FSWs in the six regional headquarter towns was estimated to be 11.8% (95% CI: 7.9–17.1); MSM was 3.4% [95% CI: 1.9–5.8]; TGs was 4.2% (95% CI: 2.9–6.1); PWIDs was 4.2% (95% CI: 2.7–6.4) and PI was 3.7% (95% CI: 1.4–9.6). The correlates of HIV test positivity among KPs and PIs include HIV-related knowledge, marital status, district, income, age and sex of KP, level of education, alcohol intake, injecting drugs, and use of lubricants. HIV prevalence is relatively high among FSWs, MSMs, PWID, and TGs as compared to the previous estimate of the general population. There is a need to scale up and strengthen evidence-based HIV prevention interventions such Pre-Exposure Prophylaxis and needle and syringe exchange programmes targeting KPs, including prison inmates. Government must scale up both non-clinical and clinical routine HIV and STI testing and counseling services at the correctional center and drop-in centers for KPs screening/testing, and ensure that services are responsive to the needs of KP.