Journal of evaluation in clinical practice
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The Hamilton depression rating scale (HDRS) is seen as an international gold standard for the measurement of depression. High rates of untreated depression, including perinatal depression, support the rationale to adapt and validate a structured version of the HDRS to be used by non-clinicians in low-income settings. ⋯ The AFFIRM-HDRS is adequately structured to be used by non-clinicians in an isiXhosa speaking perinatal population. It is hoped that this structured tool can be used to assist with identification and referral of these at-risk populations by non-clinicians in resource-constrained environments, thereby playing a role in addressing the treatment gap for perinatal depression in LMICs.
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Our purpose is to assess epidemiological agent-based models-or ABMs-of the SARS-CoV-2 pandemic methodologically. The rapid spread of the outbreak requires fast-paced decision-making regarding mitigation measures. However, the evidence for the efficacy of non-pharmaceutical interventions such as imposed social distancing and school or workplace closures is scarce: few observational studies use quasi-experimental research designs, and conducting randomized controlled trials seems infeasible. Additionally, evidence from the previous coronavirus outbreaks of SARS and MERS lacks external validity, given the significant differences in contagiousness of those pathogens relative to SARS-CoV-2. To address the pressing policy questions that have emerged as a result of COVID-19, epidemiologists have produced numerous models that range from simple compartmental models to highly advanced agent-based models. These models have been criticized for involving simplifications and lacking empirical support for their assumptions. ⋯ Given this, we claim that the best epidemiological ABMs are models of actual mechanisms and deliver both mechanistic and difference-making evidence. Consequently, they may also adequately describe the effects of possible interventions. Finally, we discuss the limitations of ABMs and put forward policy recommendations.
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The COVID-19 has posed a wide range of urgent questions: about the disease, testing, immunity, treatments, and outcomes. Extreme situations, such as pandemics, call for exceptional measures. However, this threatens the production and application of evidence. ⋯ In order to avoid fake facts and to provide sustainable solutions, we need to pay attention to the various kinds of uncertainty. Producing high-quality evidence is the solution, not the problem.