Building Capacity Through a Regranting Strategy: Promising Approaches and Emerging Outcomes

This is an evaluation report on the Community Leadership Project (CLP) in which 27 well-established intermediary organizations--community foundations, grantmaking public charities, and funder affinity groups--regrant to smaller organizations to provide financial support and tailored organizational assistance and coaching to small to mid-size organizations; technical assistance; and leadership development.The evaluation is interested in understanding not only the impact of CLP on leaders, organizations, intermediaries, and foundation partners, but also the key lessons on: (1) reaching and providing capacity-building supports to organizations and leaders serving low-income communities and communities of color; (2) characteristics of effective, culturally relevant, and community-responsive capacity building; and (3) which kinds of capacity-building supports are most effective for small and mid-sized organizations serving low-income communities and communitiesof color

Troubling the Null Curriculum through a Multiple-Perspectives Pedagogy: A Critical Dialogue Between Two Equity-Minded Teacher Educators

In this article, the authors explore the ways by which they, as equity-minded teacher educators, have introduced predominantly White pre-service teachers to the notion of a multiple-perspectives pedagogy as a vehicle to promote critical thinking and multicultural integration. The conceptual framework charts a new course for theorizing the various ideological challenges that arise when attempting to model a multiple-perspectives pedagogy to critique various aspects of the null curriculum in PK-12 and teacher education as it relates to integrating multicultural perspectives. Through critical reflection and dialogic interviews, the authors discuss how they have negotiated the various challenges and possibilities of implementing a multiple-perspectives pedagogical approach in teacher-education courses to critique the null curriculum. Implications are offered for practice and theory

Fruit scent and observer colour vision shape food-selection strategies in wild capuchin monkeys

The senses play critical roles in helping animals evaluate foods, including fruits that can change both in colour and scent during ripening to attract frugivores. Although numerous studies have assessed the impact of colour on fruit selection, comparatively little is known about fruit scent and how olfactory and visual data are integrated during foraging. We combine 25 months of behavioural data on 75 wild, white-faced capuchins (Cebus imitator) with measurements of fruit colours and scents from 18 dietary plant species. We show that frequency of fruit-directed olfactory behaviour is positively correlated with increases in the volume of fruit odours produced during ripening. Monkeys with red-green colour blindness sniffed fruits more often, indicating that increased reliance on olfaction is a behavioural strategy that mitigates decreased capacity to detect red-green colour contrast. These results demonstrate a complex interaction among fruit traits, sensory capacities and foraging strategies, which help explain variation in primate behaviour.https://www.nature.com/articles/s41467-019-10250-9Published versio

California Census 2020 Statewide Funders Initiative Final Evaluation Report

The 2020 census was among the most fraught in recent history, with threats to a fair and complete count posed by the global pandemic and the federal administration's attempt to limit the inclusion of immigrants. Fortunately, funders and other stakeholders built on the lessons of census 2010, and the California Census 2020 Statewide Funders Initiative coordinated investments with the state to maximize the number of Californians counted. This report documents learnings from the California Census 2020 Statewide Funders Initiative

Nel positively regulates the genesis of retinal ganglion cells by promoting their differentiation and survival during development

Peer reviewedPublisher PD

Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level

Background: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources. Methods: We made weekly forecasts of daily COVID-19 hospital admissions for National Health Service (NHS) Trusts in England between August 2020 and April 2021 using three disease-agnostic forecasting models: a mean ensemble of autoregressive time series models, a linear regression model with 7-day-lagged local cases as a predictor, and a scaled convolution of local cases and a delay distribution. We compared their point and probabilistic accuracy to a mean-ensemble of them all and to a simple baseline model of no change from the last day of admissions. We measured predictive performance using the weighted interval score (WIS) and considered how this changed in different scenarios (the length of the predictive horizon, the date on which the forecast was made, and by location), as well as how much admissions forecasts improved when future cases were known. Results: All models outperformed the baseline in the majority of scenarios. Forecasting accuracy varied by forecast date and location, depending on the trajectory of the outbreak, and all individual models had instances where they were the top- or bottom-ranked model. Forecasts produced by the mean-ensemble were both the most accurate and most consistently accurate forecasts amongst all the models considered. Forecasting accuracy was improved when using future observed, rather than forecast, cases, especially at longer forecast horizons. Conclusions: Assuming no change in current admissions is rarely better than including at least a trend. Using confirmed COVID-19 cases as a predictor can improve admissions forecasts in some scenarios, but this is variable and depends on the ability to make consistently good case forecasts. However, ensemble forecasts can make forecasts that make consistently more accurate forecasts across time and locations. Given minimal requirements on data and computation, our admissions forecasting ensemble could be used to anticipate healthcare needs in future epidemic or pandemic settings

Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society\u27s responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak

The impact of COVID-19 vaccination in prisons in England and Wales : a metapopulation model

Background: High incidence of cases and deaths due to coronavirus disease 2019 (COVID-19) have been reported in prisons worldwide. This study aimed to evaluate the impact of different COVID-19 vaccination strategies in epidemiologically semi-enclosed settings such as prisons, where staff interact regularly with those incarcerated and the wider community. Methods: We used a metapopulation transmission-dynamic model of a local prison in England and Wales. Two-dose vaccination strategies included no vaccination, vaccination of all individuals who are incarcerated and/or staff, and an age-based approach. Outcomes were quantified in terms of COVID-19-related symptomatic cases, losses in quality-adjusted life-years (QALYs), and deaths. Results: Compared to no vaccination, vaccinating all people living and working in prison reduced cases, QALY loss and deaths over a one-year period by 41%, 32% and 36% respectively. However, if vaccine introduction was delayed until the start of an outbreak, the impact was negligible. Vaccinating individuals who are incarcerated and staff over 50 years old averted one death for every 104 vaccination courses administered. All-staff-only strategies reduced cases by up to 5%. Increasing coverage from 30 to 90% among those who are incarcerated reduced cases by around 30 percentage points. Conclusions: The impact of vaccination in prison settings was highly dependent on early and rapid vaccine delivery. If administered to both those living and working in prison prior to an outbreak occurring, vaccines could substantially reduce COVID-19-related morbidity and mortality in prison settings