Identifying Nontraditional Epidemic Disease Risk Factors Associated with Major Health Events from World Health Organization and World Bank Open Data

Health events emerge from host, community, environment, and pathogen factors-forecasting epidemics is a complex task. We describe an exploratory analysis to identify economic risk factors that could aid epidemic risk assessment. A line list was constructed using the World Health Organization Disease Outbreaks News (2016-2018) and economic indicators from the World Bank. Poisson regression employing forward imputations was used to establish relationships with the frequency with which countries reported public health events. Economic indicators demonstrated strong performance appropriate for further assessment in surveillance programming. In our analysis, three economic indicators were significantly associated to event reporting: how much the country\u27s urban population changed, its average forest area, and a novel economic indicator we developed that assessed how much the gross domestic product changed per capita. Other economic indicators performed less well: changes in total, female, urban, and rural population sizes; population density; net migration; change in per cent forest area; total forest area; and another novel indicator, change in percent of trade as a fraction of the total economy. We then undertook a further analysis of the start of the current COVID-19 pandemic that revealed similar associations, but confounding by global disease burden is likely. Continued development of forecasting approaches capturing information relevant to whole-of-society factors (e.g., economic factors as assessed in our study) could improve the risk management process through earlier hazard identification and inform strategic decision processes in multisectoral strategies to preventing, detecting, and responding to pandemic-threat events

Identifying Nontraditional Epidemic Disease Risk Factors Associated with Major Health Events from World Health Organization and World Bank Open Data

Health events emerge from host, community, environment, and pathogen factors-forecasting epidemics is a complex task. We describe an exploratory analysis to identify economic risk factors that could aid epidemic risk assessment. A line list was constructed using the World Health Organization Disease Outbreaks News (2016-2018) and economic indicators from the World Bank. Poisson regression employing forward imputations was used to establish relationships with the frequency with which countries reported public health events. Economic indicators demonstrated strong performance appropriate for further assessment in surveillance programming. In our analysis, three economic indicators were significantly associated to event reporting: how much the country\u27s urban population changed, its average forest area, and a novel economic indicator we developed that assessed how much the gross domestic product changed per capita. Other economic indicators performed less well: changes in total, female, urban, and rural population sizes; population density; net migration; change in per cent forest area; total forest area; and another novel indicator, change in percent of trade as a fraction of the total economy. We then undertook a further analysis of the start of the current COVID-19 pandemic that revealed similar associations, but confounding by global disease burden is likely. Continued development of forecasting approaches capturing information relevant to whole-of-society factors (e.g., economic factors as assessed in our study) could improve the risk management process through earlier hazard identification and inform strategic decision processes in multisectoral strategies to preventing, detecting, and responding to pandemic-threat events

Measures of Longitudinal Immune Dysfunction and Risk of AIDS and Non-AIDS Defining Malignancies in Antiretroviral Treated People With Human Immunodeficiency Virus (HIV)

Background: Human immunodeficiency virus (HIV) infection leads to chronic immune activation/inflammation that can persist in virally suppressed persons on fully active antiretroviral therapy (ART) and increase risk of malignancies. The prognostic role of low CD4:CD8 ratio and elevated CD8 cell counts on the risk of cancer remains unclear. Methods: We investigated the association of CD4:CD8 ratio on the hazard of non-AIDS defining malignancy (NADM), AIDS-defining malignancy (ADM) and most frequent group of cancers in ART-treated people with HIV (PWH) with a CD4 and CD8 cell counts and viral load measurements at baseline. We developed Cox proportional hazard models with adjustment for known confounders of cancer risk and time-dependent cumulative and lagged exposures of CD4:CD8 ratio to account for time-evolving risk factors and avoid reverse causality. Results: CD4:CD8 ratios below 0.5, compared to above 1.0, were independently associated with a 12-month time-lagged higher risk of ADM and infection-related malignancies (adjusted hazard ratio 2.61 [95% confidence interval {CI }1.10-6.19] and 2.03 [95% CI 1.24-3.33], respectively). CD4 cell counts below 350 cells/μL were associated with an increased risk of NADMs and ADMs, as did infection, smoking, and body mass index-related malignancies. Conclusions: In ART-treated PWH low CD4:CD8 ratios were associated with ADM and infection-related cancers independently from CD4 and CD8 cell counts and may alert clinicians for cancer screening and prevention of NADM

Measures of Longitudinal Immune Dysfunction and Risk of AIDS and Non-AIDS Defining Malignancies in Antiretroviral Treated People With Human Immunodeficiency Virus (HIV)

BACKGROUND: Human immunodeficiency virus (HIV) infection leads to chronic immune activation/inflammation that can persist in virally suppressed persons on fully active antiretroviral therapy (ART) and increase risk of malignancies. The prognostic role of low CD4:CD8 ratio and elevated CD8 cell counts on the risk of cancer remains unclear. METHODS: We investigated the association of CD4:CD8 ratio on the hazard of non-AIDS defining malignancy (NADM), AIDS-defining malignancy (ADM) and most frequent group of cancers in ART-treated people with HIV (PWH) with a CD4 and CD8 cell counts and viral load measurements at baseline. We developed Cox proportional hazard models with adjustment for known confounders of cancer risk and time-dependent cumulative and lagged exposures of CD4:CD8 ratio to account for time-evolving risk factors and avoid reverse causality. RESULTS: CD4:CD8 ratios below 0.5, compared to above 1.0, were independently associated with a 12-month time-lagged higher risk of ADM and infection-related malignancies (adjusted hazard ratio 2.61 [95% confidence interval {CI }1.10-6.19] and 2.03 [95% CI 1.24-3.33], respectively). CD4 cell counts below 350 cells/μL were associated with an increased risk of NADMs and ADMs, as did infection, smoking, and body mass index-related malignancies. CONCLUSIONS: In ART-treated PWH low CD4:CD8 ratios were associated with ADM and infection-related cancers independently from CD4 and CD8 cell counts and may alert clinicians for cancer screening and prevention of NADM

Integrase Strand Transfer Inhibitor Use and Cancer Incidence in a Large Cohort Setting

Background: Limited data exist examining the association between incident cancer and cumulative integrase inhibitor (INSTI) exposure. Methods: Participants were followed from baseline (latest of local cohort enrollment or January 1, 2012) until the earliest of first cancer, final follow-up, or December 31, 2019. Negative binomial regression was used to assess associations between cancer incidence and time-updated cumulative INSTI exposure, lagged by 6 months. Results: Of 29 340 individuals, 74% were male, 24% were antiretroviral treatment (ART)-naive, and median baseline age was 44 years (interquartile range [IQR], 36-51). Overall, 13 950 (48%) individuals started an INSTI during follow-up. During 160 657 person-years of follow-up ([PYFU] median 6.2; IQR, 3.9-7.5), there were 1078 cancers (incidence rate [IR] 6.7/1000 PYFU; 95% confidence interval [CI], 6.3-7.1). The commonest cancers were non-Hodgkin lymphoma (n=113), lung cancer (112), Kaposi's sarcoma (106), and anal cancer (103). After adjusting for potential confounders, there was no association between cancer risk and INSTI exposure (≤6 months vs no exposure IR ratio: 1.15 [95% CI, 0.89-1.49], >6-12 months; 0.97 [95% CI, 0.71-1.32], >12-24 months; 0.84 [95% CI, 0.64-1.11], >24-36 months; 1.10 [95% CI, 0.82-1.47], >36 months; 0.90 [95% CI, 0.65-1.26] [P=.60]). In ART-naive participants, cancer incidence decreased with increasing INSTI exposure, mainly driven by a decreasing incidence of acquired immune deficiency syndrome cancers; however, there was no association between INSTI exposure and cancer for those ART-experienced (interaction P<.0001). Conclusions: Cancer incidence in each INSTI exposure group was similar, despite relatively wide CIs, providing reassuring early findings that increasing INSTI exposure is unlikely to be associated with an increased cancer risk, although longer follow-up is needed to confirm this finding