Effect of COVID-19 pandemic on home delivery of contraceptives by community health workers in India
Bibliographic record
Abstract
The World Health Organization (WHO) declared COVID-19 a global health emergency in January 2020, leading to a nationwide lockdown in India. It has been an experience from other outbreaks that governments cannot maintain the essential health services and guarantee health services. Due to COVID-19-related case management, all health schemes, including FP services, have been disrupted globally regarding availability, accessibility, appropriateness of service delivery, adequacy, and continuity of care. The impact of the pandemic on FP services listed includes disruptions in supply chain management, enhanced gender inequity, communication barriers, fear of going outside and buying contraceptives, discontinuity of ASHA capacity building, increased time spent with all family members, reverse migration of workers, and increased need of contraceptive commodities. Evidence shows the consequence of non-supply of logistics, social distancing, inadequate human resources, and inability to access services might result in 26 million couples in unmet need for contraception, resulting in 2.4 million unintended pregnancies and 1.45 million abortions, which may lead to unsafe abortions. Potential solutions to these problems include telephonic service delivery, maintaining a record, using video communication and other technological solutions using a smartphone, combining routine immunization with FP services, and installing self-dispensing machines for contraceptives at accessible places. The limitation of this work is that this is wholly experienced-based work and not based on primary findings from the field level data. These findings highlight the importance of reproductive health needs during the pandemic and guide policymakers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".