Travel-associated Diseases, Indian Ocean Islands, 1997–2010
Bibliographic record
Abstract
Data collected by the GeoSentinel Surveillance Network for 1,415 ill travelers returning from Indian Ocean islands during 1997-2010 were analyzed.Malaria (from Comoros and Madagascar), acute nonparasitic diarrhea, and parasitoses were the most frequently diagnosed infectious diseases.An increase in arboviral diseases reflected the 2005 outbreak of chikungunya fever.T he outbreak of chikungunya fever in Indian Ocean islands (IOI) provides new insights on emerging infections in this geographic region (1).We present data collected over 14 years from travelers to IOI who visited GeoSentinel clinics. The StudyGeoSentinel sites are specialized travel clinics providing surveillance data for ill travelers.Detailed methods for recruitment of patients for the GeoSentinel database are described elsewhere (2).Demographics, travel characteristics, and individual medical data were obtained from travelers to Comoros (including Mayotte), Madagascar, Maldives, Mauritius, Réunion Island, and Seychelles during March 1, 1997-December 31, 2010.Statistical significance was determined by using Fisher exact test for categorical variables and Kruskal-Wallis test for quantitative variables.A 2-sided significance level of p<0.05 was considered significant.This study comprised 1,415 ill patients (Table 1).Demographic data varied according to the visited island.Median age was 36 years, and the male to female ratio was 1.1:1.0.The most common reason for travel was tourism (44.5%), followed by visiting friends and relatives (VFR) (30.8%).Only 43.0% of travelers had a pre-travel encounter with a travel medicine specialist or general practitioner.Illness patterns varied by place of exposure (Figure 1).Malaria, the most frequently diagnosed illness (388 [27.4%] travelers), accounted for 74.1% of diagnoses for VFR but only 6.6% for non-VFR travelers (p<0.01).Plasmodium falciparum malaria represented 88.0% of cases, including 12 cases of severe malaria, mostly from Comoros or Madagascar.One case of P. ovale malaria was reported from Mauritius in a person who had previously traveled to Cameroon.Arboviral disease diagnoses included 40 cases of chikungunya and 24 cases of dengue.Overall, arboviral diseases accounted for 4.5% of the total diagnoses.Arboviral diseases accounted for 36.0% of diseases acquired by travelers to Réunion Island (vs.3.6% in non-Réunion Island travelers, p<0.01) and were more frequent in tourists than in nontourists (6.5% vs. 2.9%, p<0.01).Numbers of arboviral diseases showed a sustained increase and peaked in 2006.Dengue was noted only after 2001.Chikungunya cases dramatically increased in 2006 and were sustained at a lower level during 2007-2010, suggesting local transformation from epidemic to endemic phases or better notification of the diagnosis (Figure 2).Parasitic infections other than malaria accounted for 131 (9.3%) diagnoses.A higher proportion of parasitoses occurred in travelers to Madagascar than in persons who had not traveled there (21.3% vs. 2.6%, p<0.01) and in missionary than non-missionary travelers (18.7% vs. 7.9%, p<0.01).Intestinal helminths or protozoans were the most commonly identified parasites.Schistosomiasis (21 cases) was reported from Madagascar only.Acute nonparasitic diarrhea accounted for 162 (11.5%) final diagnoses.Higher proportions of such diarrhea occurred in travelers to Madagascar than in persons who had not traveled there (15.7% vs. 9.1%, p<0.01) and in travelers to Maldives than in persons who had not traveled there (18.4% vs. 10.5%, p<0.01).In 23 (14.2%) cases, a pathogen was identified.Acute nonparasitic diarrhea and skin infections were more frequently reported in tourists than in nontourists (17.3% and 12.4% vs. 6.8% and 3.8%, respectively [p<0.01]).The proportion of respiratory infections
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".