Emerging infectious diseases and outbreaks: implications for women’s reproductive health and rights in resource-poor settings
Bibliographic record
Abstract
This century is witnessing dramatic changes in the health needs of the world's populations. The double burden of infectious and chronic diseases constitutes major causes of morbidity and mortality. Over the last two decades, there has been a rise in infectious diseases, including the severe acute respiratory syndrome virus (SARS), the H1N1 pandemic influenza, the Ebolavirus and the Covid-19 virus. These diseases have rapidly spread across the world and have reminded us of the unprecedented connectivity that defines our modern civilization. Though some countries have made substantial progress toward improving global surveillance for emerging infectious diseases (EIDs), the vast majority of Low-and Middle-income Countries (LMICs) with fragile health systems and various system-related bottlenecks remain vulnerable to outbreaks and, as such, experience dramatic social and economic consequences when they are reported. Lessons learned from past outbreaks suggest that gender inequalities are common across a range of health issues relating to Sexual and Reproductive Health and Rights (SRHR), with women being particularly disadvantaged, partially due to the burden placed on them. Though these countries are striving to improve their health systems and be more inclusive to this vulnerable group, the national/ global outbreaks have burdened the overall system and thus paralyzed normal services dedicated to the delivery of Sexual and Reproductive Health (SRH) services. In this paper, we discuss the global commitments to SRH, the impact of the EIDs on the LMICs, the failure in the delivery of SRH services, and the strategies for successful implementation of recovery plans that must address the specific and differentiated needs of women and girls in resource-poor settings.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".