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Background Although surveillance systems used to mitigate disasters serve essential public health functions, communities of color have experienced disproportionate harms (eg, criminalization) as a result of historic and enhanced surveillance. Methods To address this, we developed and piloted a novel, equity-based scoring system to evaluate surveillance systems regarding their potential and actual risk of adverse effects on communities made vulnerable through increased exposure to policing, detention/incarceration, deportation, and disruption of access to social services or public resources. To develop the scoring system, we reviewed the literature and surveyed an expert panel on surveillance to identify specific harms (eg, increased policing) that occur through surveillance approaches. Results Scores were based on type of information collected (individual and/or neighborhood level) and evidence of sharing information with law enforcement. Scores were 0 (no risk of harm identified), 1 (potential for risk), 2 (evidence of risk), and U (data not publicly accessible). To pilot the scoring system, 44 surveillance systems were identified between June 2020 and October 2020 through an environmental scan of systems directly related to COVID-19 (n=21), behavioral and health-related services (n=11), and racism and racism-related factors (n=12). A score of 0-2 was assigned to 91% (n=40) of the systems; 9% were scored U; 30% (n=13) scored a 0. Half scored a 1 (n=22), indicating a “potential for the types of harm of concern in this analysis.” “Evidence of harm,” a score of 2, was found for 12% (n=5). Conclusions The potential for surveillance systems to compromise the health and well-being of racialized and/or vulnerable populations has been understudied. This project developed and piloted a scoring system to accomplish this equity-based imperative. The nobler pursuits of public health to improve the health for all must be reconciled with these potential harms.

Air pollution is one of the leading risk factors for poor health in Africa, resulting in millions of premature deaths and economic losses. Of particular interest is exposure to fine particulate matter (PM2.5) which is the driver for a majority of deaths across the continent. However, PM monitoring, and by extension, ground-level data on PM2.5 is very limited; this limits our understanding of the widespread societal and health impacts linked to PM pollution. The robustness of low-cost PM sensors and their ability to report in situ data in tropical environments via internet-based platforms as well as relative affordability has created the opportunity to employ low-cost sensors (LCS) for air quality monitoring but calibration methodologies and the usefulness of the high-temporal resolution data for source identification remain a challenge. Increasingly, local governments in African countries are also turning to low-cost sensors to monitor air quality. In this study, two Airnote PM monitors were colocated with reference-grade Teledyne PM mass monitor T640 for ~4 weeks at the University of Ghana, Accra to establish their performance using a simplified data correction methodology - multiple linear regression (MLR) model. A split ratio of 80% and 20% was used to train and test the populated Airnote PM2.5 data respectively based on measurements from Teledyne T640 with temperature and relative humidity values from the Airnote monitor. Sectoral and calendar analysis with wind component data were used to triangulate the sources of PM2.5. We observed a high consistency between the two Airnote monitors. Hourly and 24-hour average PM2.5 values ranged from 25 to 95 μg/m3, and 29 to 54 μg/m3 respectively, and in most cases, were significantly higher than the WHO Air Quality Guideline. MLR using Pearson’s correlation analysis improved the out-of-the-box quality of low-cost Airnote PM2.5 data; the R2 improved from 0.69 to 0.84 and the mean absolute error from 11.75 to 4.20 μg/m3 respectively. Also, the MLR correction model was found to improve the Airnote PM2.5 data quality for higher relative humidity (between 50 and 90%) but not lower. PM2.5 pollution was local and from N, NE and SW winds for the raw, corrected and Teledyne PM mass monitor T640 measurements. Together, these results indicate that with appropriate corrections, low-cost PM sensors can generate the much needed data for air pollution research and mitigation in areas with limited air quality monitoring and data.

Inadequate attention to racial health equity is a common challenge to effective, reliable monitoring and mitigation of COVID-19 disparities. Efforts to monitor and miti­gate COVID-19 disparities continue to be hampered by inadequacies in how surveil­lance systems collect, tabulate, and report COVID-19-related outcomes. We conduct­ed environmental scans of existing public health surveillance systems and reporting standards, literature reviews, focus groups with surveillance experts, and consulta­tions with the Centers for Disease Control and Prevention (CDC) and an expert panel on surveillance to identify and explore strengths, weaknesses, and gaps in how ex­isting systems monitor COVID-19 and their implications for addressing disparities in related outcomes. We present recommen­dations based on these reviews and propose a core minimum set of health indicators and best-practice standards for reporting these indicators by COVID-19 surveillance sys­tems to monitor racial/ethnic and other dis­parities in the pandemic. These recommen­dations are relevant to monitoring disparities in the ongoing COVID-19 pandemic and may inform monitoring of future epidemics. This discussion is part of an effort by Project REFOCUS to develop syndemic surveil­lance systems for monitoring the intersecting pandemics of COVID-19 and racism. Ethn Dis. 2022;32(2):151-164; doi:10.18865/ed.32.2.151

The populations impacted most by COVID are also impacted by racism and related social stigma; however, traditional surveillance tools may not capture the intersectionality of these relationships. We conducted a detailed assessment of diverse surveillance systems and databases to identify characteristics, constraints and best practices that might inform the development of a novel COVID surveillance system that achieves these aims. We used subject area expertise, an expert panel and CDC guidance to generate an initial list of N > 50 existing surveillance systems as of 29 October 2020, and systematically excluded those not advancing the project aims. This yielded a final reduced group (n = 10) of COVID surveillance systems (n = 3), other public health systems (4) and systems tracking racism and/or social stigma (n = 3, which we evaluated by using CDC evaluation criteria and Critical Race Theory. Overall, the most important contribution of COVID-19 surveillance systems is their real-time (e.g., daily) or near-real-time (e.g., weekly) reporting; however, they are severely constrained by the lack of complete data on race/ethnicity, making it difficult to monitor racial/ethnic inequities. Other public health systems have validated measures of psychosocial and behavioral factors and some racism or stigma-related factors but lack the timeliness needed in a pandemic. Systems that monitor racism report historical data on, for instance, hate crimes, but do not capture current patterns, and it is unclear how representativeness the findings are. Though existing surveillance systems offer important strengths for monitoring health conditions or racism and related stigma, new surveillance strategies are needed to monitor their intersecting relationships more rigorously.

For many years the cost of health care in sub-Saharan Africa was largely covered by the State. But in September 1987, in view of the economical problems those countries had to face, the WHO regional committee adopted the "Bainako's Initiative" resolution. This meant that from then on everybody was to pay for their health expenses. The purpose of this prospective study which was conducted from March 1, 1996 to February 28, 1999 among 316 patients was to assess hospitalization charges incurred for patients in the Neurology Department of Lomé Teaching Hospital with a view to improve the quality of the services provided and the accessibility of care. A questionnaire was used and every expense relating to the hospitalization of each patient was recorded on a daily basis. The average cost is 389,586 (48,485 FCFA for an average stay of 19.7 (2.5 days. This average cost is 19 times the minimal monthly salary of a state employee. It can be broken down as follows: Accommodation costs represent 52%, medical acts and tests 20.3% while drug costs amount to 21.2% and accompanist expenses represent 6.5%. The average cost of HIV-infected patients is 635,017 (190,624 FCFA for an average stay of 57 (12.9 days. The average cost of HIV-negative patients is 257,354 (12,837 FCFA for an average stay of 24.4 (1.8 days. To improve the quality of the services and the accessibility of care, it is necessary to prescribe and make drugs available in their generic form. After a few days in hospital, some disabling diseases as strokes, myelopathy and myopathy should be treated at home to reduce the length of stay in hospital or in cheaper places such as prolonged accommodation centres.

SUMMARYThis study investigated the effect of maternal Onchocerca volvulus infection on humoral and cellular responsiveness in newborn children and their mothers. Onchocerca volvulus-specific IgG isotypes and IgE were significantly elevated in infected mothers and their infants. One year post partum, O. volvulus-specific IgG4 was strongly reduced in children of infected mothers, while IgG1 responses weakened only slightly. Umbilical cord mononuclear blood cells (UCBC) and peripheral blood cells (PBMC) from mothers proliferated in response to phytohaemagglutinin (PHA), concanavalin A (Con A), and the bacterial antigens streptolysin-O (SL-O) or purified protein derivative (PPD). UCBC from neonates born to O. volvulus-infected mothers responded lower (P