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Record W2000183495 · doi:10.2149/tmh.32.305

SEROEPIDEMIOLOGY OF DENGUE AND ASSESSMENT OF PUBLIC AWARENESS IN THE DOMINICAN REPUBLIC

2004· article· en· W2000183495 on OpenAlexfundno aff
Yoshihiro Makino, AKIHISA SHICHIJO, CASTRO BELLO, Yuki Eshita, Mildre Disla, ANA JULIA CESIN, BARBARA GALCIA, Miguel Lora, Sonia Valdez, Jose D. J. Diaz Aquino, Hiroshi Aono, SHAO-PING MA, Masazumi Takeshita

Bibliographic record

VenueTropical Medicine and Health · 2004
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersJapan International Cooperation AgencyEgg Farmers of Canada
KeywordsDengue feverPublic healthMedicineEnvironmental healthSerotypeDemographyImmunology

Abstract

fetched live from OpenAlex

Dengue fever (DF) is a major public health concern in the Dominican Republic. In recent years, several epidemics of DF have been reported to the Pan American Health Office (PAHO), but the extent of the epidemics has not been clearly understood yet. Therefore, we conducted a nationwide seroepidemiology of dengue (DEN) infection. At the same time, we conducted an interview survey to assess public awareness regarding the disease. The serum samples were collected at seven main cities in the Dominican Republic and screened for DEN antibody with a commercial ELISA kit. A total of 2007 serum specimens were examined. The prevalence of DEN antibody in the seven cities varied between 43.1 and 89.7%. Neutralization (N) test carried out on the ELISA-positive serum from Samana, one of the high antibody-prevalent cities, revealed that all the sera showed positive to at least two DEN serotypes. Geometric mean N titers against DEN-1, 2, 3 and 4 were 40.5, 463.7, 59.9 and 454.4 respectively. No difference in antibody prevalence was observed between males and females. It appeared that a high level of awareness regarding DF did little affect DEN prevalence. Strong, concrete public health strategies that motivate the local community to combat DF are required.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.162
GPT teacher head0.468
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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