Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia I. Patterns of lagged weather effects reflect biological mechanisms

BACKGROUND: Malaria epidemics due to Plasmodium falciparum are reported frequently in the East African highlands with high case fatality rates. There have been formal attempts to predict epidemics by the use of climatic variables that are predictors of transmission potential. However, little consensus has emerged about the relative importance and predictive value of different factors. Understanding the reasons for variation is crucial to determining specific and important indicators for epidemic prediction. The impact of temperature on the duration of a mosquito's life cycle and the sporogonic phase of the parasite could explain the inconsistent findings. METHODS: Daily average number of cases was modeled using a robust Poisson regression with rainfall, minimum temperature and maximum temperatures as explanatory variables in a polynomial distributed lag model in 10 districts of Ethiopia. To improve reliability and generalizability within similar climatic conditions, we grouped the districts into two climatic zones, hot and cold. RESULTS: In cold districts, rainfall was associated with a delayed increase in malaria cases, while the association in the hot districts occurred at relatively shorter lags. In cold districts, minimum temperature was associated with malaria cases with a delayed effect. In hot districts, the effect of minimum temperature was non-significant at most lags, and much of its contribution was relatively immediate. CONCLUSIONS: The interaction between climatic factors and their biological influence on mosquito and parasite life cycle is a key factor in the association between weather and malaria. These factors should be considered in the development of malaria early warning system

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions

BACKGROUND: Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. METHODS: Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4(th)-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. RESULTS: The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10–25% more cases at a given sensitivity in cold districts than in hot ones. CONCLUSIONS: The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems

Impact of genomic testing and patient-reported outcomes on receipt of adjuvant chemotherapy

Practice guidelines incorporate genomic tumor profiling, using results such as the Oncotype DX Recurrence Score (RS), to refine recurrence risk estimates for the large proportion of breast cancer patients with early-stage, estrogen receptor-positive disease. We sought to understand the impact of receiving genomic recurrence risk estimates on breast cancer patients’ well-being and the impact of these patient-reported outcomes on receipt of adjuvant chemotherapy. Participants were 193 women (mean age 57) newly diagnosed with early-stage breast cancer. Women were interviewed before and 2–3 weeks after receiving the RS result between 2011 and 2015. We assessed subsequent receipt of chemotherapy from chart review. After receiving their RS, perceived pros (t = 4.27, P < .001) and cons (t = 8.54, P <.001) of chemotherapy increased from pre-test to post-test, while perceived risk of breast cancer recurrence decreased (t = 2.90, P = .004). Women with high RS tumors were more likely to receive chemotherapy than women with low RS tumors (88 vs. 5 %, OR 0.01, 0.00–0.02, P < .001). Higher distress (OR 2.19, 95 % CI 1.05–4.57, P < .05) and lower perceived cons of chemotherapy (OR 0.50, 95 % CI 0.26–0.97, P < .05) also predicted receipt of chemotherapy. Distressed patients who saw few downsides of chemotherapy received this treatment. Clinicians should consider these factors when discussing chemotherapy with breast cancer patients

On the well-posedness of the stochastic Allen-Cahn equation in two dimensions

White noise-driven nonlinear stochastic partial differential equations (SPDEs) of parabolic type are frequently used to model physical and biological systems in space dimensions d = 1,2,3. Whereas existence and uniqueness of weak solutions to these equations are well established in one dimension, the situation is different for d \geq 2. Despite their popularity in the applied sciences, higher dimensional versions of these SPDE models are generally assumed to be ill-posed by the mathematics community. We study this discrepancy on the specific example of the two dimensional Allen-Cahn equation driven by additive white noise. Since it is unclear how to define the notion of a weak solution to this equation, we regularize the noise and introduce a family of approximations. Based on heuristic arguments and numerical experiments, we conjecture that these approximations exhibit divergent behavior in the continuum limit. The results strongly suggest that a series of published numerical studies are problematic: shrinking the mesh size in these simulations does not lead to the recovery of a physically meaningful limit.Comment: 21 pages, 4 figures; accepted by Journal of Computational Physics (Dec 2011

Culturally targeted video improves psychosocial outcomes in latina women at risk of hereditary breast and ovarian cancer

Latina women at risk of hereditary breast and ovarian cancer (HBOC) have lower awareness, knowledge, and use of genetic counseling and testing services (GCT) than non-Latina Whites. Few interventions have been developed to reduce these disparities among at-risk Latinas. This pilot study assessed the impact of a culturally targeted narrative video developed by our team. The study included 40 Latina immigrants living in the United States who were at risk of HBOC, including a ected and una ected women. We assessed pre-post di erences in psychosocial outcomes. Participants were 47.35 years old on average (SD = 9.48). Most (70%) were una ected with cancer, had an annual income of $40,000 or less (65%), an education of High School or less (62.5%), and were uninsured (77.5%). The video significantly enhanced knowledge (p < 0.001), positive attitudes (p < 0.05), anticipatory positive emotions (p < 0.05), and intentions to participate in counseling (p < 0.001). Importantly, the video also significantly reduced negative attitudes (p < 0.05), and attitudinal ambivalence (p < 0.001). The culturally targeted video shows preliminary evidence in improving psychosocial outcomes related to GCT uptake in Latinas at risk for HBOC. This intervention is a promising easily-disseminable strategy to address disparities in GCT utilizationThis research was funded by the National Cancer Institute (R03CA191543; Hurtado-de-Mendoza and Sheppard, MPIs). This project was also supported by Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS) by Federal Funds; the National Center for Advancing Translational Sciences (NCATS); and the National Institutes of Health (NIH), through the Clinical and Translational Science Awards Program (CTSA) (KL2TR001432; Hurtado-de-Mendoza. PI), and by the Ministry of Science, Innovation, and Universities in Spain (PGC2018-093821-B-I00, FEDER, MICINN, Carrera, PI)

Psychosocial and Quality of Life in Women Receiving the 21-Gene Recurrence Score Assay: The Impact of Decision Style in Women with Intermediate RS

Multigene assays such as the 21-gene recurrence score (RS) quantify risk for recurrence and potential benefit from chemotherapy in early-stage, ER+ breast cancers. Few studies have assessed the impact of testing on patient-reported outcomes such as cancer-related distress or quality of life. The few studies that have assessed these outcomes do not consider potential modifiers, such as the patients’ level of involvement in the treatment decision-making process. In the current study, 81 breast cancer patients who received the RS assay completed cross-sectional surveys. We used linear multiple regression to assess whether test result, decision-making role (passive versus shared/active), and their interaction contributed to current levels of distress, quality of life, and decisional conflict. There were no associations between these variables and test result or decision-making role. However, women who received an intermediate RS and took a passive role in their care reported higher-cancer-related distress and cancer worry and lower quality of life than those who took a shared or active role. These data should be confirmed in prospective samples, as these poorer outcomes could be amenable to intervention

Lead Concentrations in Relation to Multiple Biomarkers of Cardiovascular Disease: The Normative Aging Study

Background: Lead exposure has been associated with cardiovascular disease (CVD) in animal and human studies. However, the mechanisms of action have not been fully elucidated. We therefore examined the relationship between lead and multiple biomarkers of CVD