Epidemiology of Malaria in East Nusa Tenggara Province in Indonesia: Protocol for a Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Malaria is a global pandemic that results in approximately 228 million cases globally; 3.5% of these cases are in Southeast Asian countries, including Indonesia. Following the World Health Organization (WHO) initiative, Indonesia is in the process of achieving malaria-free zone status by 2030. However, the eastern part of Indonesia, including the East Nusa Tenggara Province (ENTP), still has a disproportionately high rate of malaria. OBJECTIVE: The aims of this cross-sectional study are to determine the awareness and knowledge, attitude, and practice toward various aspects of malaria among rural adults and their associated factors, including sociodemographic factors and ethnicities; assess the gap between coverage of, access to, and use of long-lasting insecticide-treated nets (LLINs) among the households; estimate the prevalence of and factors associated with malaria in rural adults; and develop a risk prediction model for malaria. METHODS: A multistage cluster sampling procedure with a systematic random sampling procedure at cluster level 4 was applied to recruit 1503 adults aged 18 years or older from the ENTP. Each participant participated in a face-to-face interview to assess their awareness and knowledge, attitude, and practice toward aspects of malaria, practices of sleeping under LLINs, and history of malaria. Information on sociodemographic, environmental, and lifestyle factors was also documented. The proportion of knowledge, attitude, and practice toward aspects of malaria and their variations across different sociodemographic and ethnic groups will be analyzed using descriptive statistics and chi-square tests. Coverage and access to LLINs will be evaluated based on the WHO recommendations. Malaria risk factors will be analyzed using logistic regression. Multilevel logistic regression will be applied to estimate the risk score for malaria. RESULTS: Of the total participants, 99.46% (1495/1503) of rural adults from 49 villages in the ENTP participated in a face-to-face interview from October to December 2019. The study results are expected to be published in peer-reviewed journals. CONCLUSIONS: The best malaria risk prediction model will be developed in this study. In this protocol, we developed a methodology to provide new evidence to guide health policy in supporting the ENTP government's expectation to achieve the malaria-free rating by 2030. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/23545.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".