Peru – Progress in health and sciences in 200 years of independence
Bibliographic record
Abstract
Peru celebrates 200 years of independence in 2021. Over this period of independent life, and despite the turbulent socio-political scenarios, from internal armed conflict to economic crisis to political instability over the last 40 years, Peru has experienced major changes on its epidemiological and population health profile. Major advancements in maternal and child health as well as in communicable diseases have been achieved in recent decades, and today Peru faces an increasing burden of non-communicable diseases including mental health conditions. In terms of the configuration of the public health system, Peru has also strived to secure country-wide optimal health care, struggling in particular to improve primary health care and intercultural services. The science and technology infrastructure has also evolved, although the need for substantial investments remains if advancing science is to be a national priority. Climate change will also bring significant challenges to population health given Peru's geographical and microclimates diversity. Looking back over the 200-years of independence, we present a summary of key advances in selected health-related fields, thus serving as the basis for reflections on pending agendas and future challenges, in order to look forward to ensuring the future health and wellbeing of the Peruvian population. Resumen translated abstract: El Perú cumple 200 años de independencia en 2021. Durante estos dos siglos de vida independiente, junto con periodos sociales y políticos turbulentos, incluyendo un conflicto armado interno, hiperinflación y la inestabilidad política de los últimos 40 años, el Perú ha experimentado importantes cambios en su perfil epidemiológico con repercusiones directas en la salud de la población. En las últimas décadas, los indicadores de salud materno-infantil y de las enfermedades transmisibles muestran mejoría importante, pero el país se enfrenta de manera simultánea a una carga cada vez mayor de enfermedades no transmisibles y de salud mental. En cuanto a los sistemas de salud pública, se han realizado esfuerzos por aumentar la cobertura y calidad de la atención de salud en todo el país, apostándose en particular por mejorar la atención primaria. La ciencia y tecnología relacionadas con la salud también han mejorado, aunque si se quiere que la ciencia sea una prioridad nacional, son necesarias inversiones sustanciales. El cambio climático traerá importantes desafíos para la salud de la población, dada la diversidad geográfica y de microclimas del país. Para conmemorar los 200 años de vida independiente del Perú, presentamos un resumen de avances clave en diversas áreas y temas relacionados con la salud. Este repaso sirve como base para reflexionar sobre agendas y desafíos pendientes y futuros, con el fin de asegurar la salud y el bienestar de la población peruana en las próximas décadas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".