OBJECTIVES: To design and perform a simple surveillance on OLP patients based on colour-coded topography mouth maps (TMM).
MATERIALS AND METHODS: Three colour-coded TMM were employed: red for OLP in high risk oral mucosal sites, yellow for cases showing improvement and green for asymptomatic lesions at each recall visit. In this preliminary study, these were applied on 30 histologically confirmed OLP individuals attending the Oral Medicine Clinic at the Department of Oral Pathology, Oral Medicine and Periodontology, Faculty of Dentistry, University of Malaya. The sites and extent of OLP lesions were charted on either red, yellow or green TMM based on defined criteria. This surveillance evaluated OLP in relation to patientandapos;s age, race, gender, underlying systemic conditions, oral habits, initial onset of OLP, oral manifestations and presence/absence of clinically suspicious areas.
RESULTS: Study sample comprised 4 (13.3%) Malays, 9 (30.0%) Chinese and 17 (56.7%) Indians. Most OLP patients belong to the green TMM (n= 14, 46.6%) group followed by red (n= 11, 36.7%) and yellow (n= 5, 16.7%) groups. Of the 11 cases with red TMM, rebiopsy was performed on 4 cases but no dysplasia was detected. Any local confounding factors namely periodontal disease or faulty dental restorations were managed accordingly.
CONCLUSIONS: TMM is simple to use and aided the clinicians in terms of time saving and patient management. Hence, follow-up of OLP patients can be carried out more efficiently and appropriately. TMM can be used for surveillance of other oral precancerous lesions and conditions.
METHODS AND FINDINGS: Our approach is based on a parsimonious mathematical model of disease transmission and only requires data collected through routine surveillance and standard case investigations. We apply it to assess the transmissibility of swine-origin influenza A H3N2v-M virus in the US, Nipah virus in Malaysia and Bangladesh, and also present a non-zoonotic example (cholera in the Dominican Republic). Estimation is based on two simple summary statistics, the proportion infected by the natural reservoir among detected cases (G) and among the subset of the first detected cases in each cluster (F). If detection of a case does not affect detection of other cases from the same cluster, we find that R can be estimated by 1-G; otherwise R can be estimated by 1-F when the case detection rate is low. In more general cases, bounds on R can still be derived.
CONCLUSIONS: We have developed a simple approach with limited data requirements that enables robust assessment of the risks posed by emerging zoonoses. We illustrate this by deriving transmissibility estimates for the H3N2v-M virus, an important step in evaluating the possible pandemic threat posed by this virus. Please see later in the article for the Editors' Summary.
MATERIALS AND METHODS: Mean SF-36 scores were calculated for 24 population subgroups (categorised by age, gender, ethnicity and questionnaire language) and for subjects with self-reported co-morbid conditions using data from a community-based survey in Singapore.
RESULTS: The English and Chinese SF-36 was completed by 4122 and 1381 subjects, respectively, 58% (n = 3188) of whom had self-reported co-morbid conditions. SF-36 scores varied in subgroups differing in age, gender and ethnicity. In general, subjects with self-reported co-morbid conditions had lower SF-36 scores than those without these conditions, the magnitude of which exceeded 20 points in several instances. A method for calculation of SF-36 scores adjusted for age, gender, ethnicity and questionnaire language is described.
CONCLUSION: We present norms for English and Chinese SF-36 versions in Singapore and describe potential uses for these data in assessing HRQOL in Singapore.
METHODS: We described the consultations by sex, age, week, and diagnosis according to the Surveillance in Post-Extreme Emergencies and Disasters system. We compared the number and proportion of upper respiratory tract infections (URTIs) with a control season in 2014.
RESULTS: We included 6785 consultations, 55.9% from women. The majority of consultations were communicable diseases (88.2%) followed by noncommunicable (7.1%) and injuries (5.6%). Males suffered more often from injuries than women (66.0% vs 34.0%). Consultations due to injuries decreased from 10.0% in the first to 2.9% in the last week. The most frequent diagnosis over the study period was acute respiratory infections (ARIs) (73.1%), of which 83.0% were children. The number of daily URTIs was higher than in a similar 2014 period.
CONCLUSIONS: ARI was the most prevalent diagnosis. We recommend ARI treatments being fully accessible after such a disaster. During the first week, injury prevention should focus on adult men. Studies after natural disasters should include control periods to better understand disease distribution, ultimately improving the prioritization in disasters.