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1.
J Public Health Manag Pract ; 29(6): 845-853, 2023.
Article in English | MEDLINE | ID: mdl-37738597

ABSTRACT

CONTEXT: Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community. PROGRAM: Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020. IMPLEMENTATION: The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard. EVALUATION: This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring. DISCUSSION: Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.


Subject(s)
COVID-19 , Wastewater , Humans , Ohio , Pandemics/prevention & control , Public Health , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2
2.
Breast Cancer Res Treat ; 90(1): 41-6, 2005 Mar.
Article in English | MEDLINE | ID: mdl-15770525

ABSTRACT

Age at treatment and the total cumulative dose of cyclophosphamide are established predictors of chemotherapy-induced ovarian failure in premenopausal women with breast cancer. In a prospective trial of 49 women receiving adjuvant chemotherapy, we sought to identify whether other factors including family history of osteoporosis, lifestyle factors, reproductive hormones, bone turnover markers, or bone mineral density (BMD) of the hip or total spine measured before (baseline) and 6 months after chemotherapy increased the risk of ovarian failure. Univariate logistic regression analyses were used to identify the variables related to the risk of ovarian failure, and a multivariate logistic regression model was used to find the best of predictors of ovarian failure among the variables. In the multivariate model a higher total spine BMD at baseline (OR=6.0, p=0.02, 95% CI 1.4-27.3), and a 10% change in estradiol (E2) from baseline to six months (OR=0.80, p=0.02, 95% CI 0.67-0.97) were predictive of ovarian failure adjusted for age. In particular, as total spine BMD at baseline increases by 0.1 g/cm2 the odds of developing chemotherapy-induced ovarian failure increases by 6-fold. The multivariate model provides a good fit to the data (GOF p-value=0.8852), and provides excellent discrimination between those women who will and will not develop ovarian failure (Area under ROC=0.9487). If confirmed in larger data sets, using baseline spinal BMD to identify women who are at higher risk of developing ovarian failure independent of their age would be of value.


Subject(s)
Antineoplastic Agents/adverse effects , Bone Density , Breast Neoplasms/drug therapy , Lumbar Vertebrae , Primary Ovarian Insufficiency/chemically induced , Primary Ovarian Insufficiency/prevention & control , Adult , Chemotherapy, Adjuvant , Female , Humans , Logistic Models , Middle Aged , Multivariate Analysis , Primary Ovarian Insufficiency/epidemiology , Risk Factors , United States/epidemiology
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