Sentence examples for prevalence predictions from inspiring English sources

Our model predictions of the prevalence in Caió are independent of population size (Fig. 1a), and given that the epidemic there appears representative of the rest of Guinea-Bissau, our prevalence predictions are relevant throughout the country.

The study was not intended to investigate prevalence, prediction rules or associations between each of the life impacts.

The population-based Prevalence, Prediction, and Prevention of Diabetes (PPP)–Botnia Study has been described in detail elsewhere (16– 16).

The Prevalence, Prediction and Prevention of Diabetes (PPP -Botnia Study is a PPP -BotniabaStudytudy is the Botnia region of Western Finland.

Prevalence, Prediction and Prevention of diabetes (PPP-Botnia) is a population-based study in the Botnia region of Western Finland (14).

Two studies from the Finnish PPP (Prevalence, Prediction and Prevention of Diabetes -Botnia program examineDiabetes -Botniaiprogramexaminedssive sympthes and glucose metabolism (12, 13).

Figure  7 illustrated active PTB prevalence prediction map (1 × 1 km spatial resolution) and prediction standard error map (1 × 1 km spatial resolution) according to the best geostatistical method.

Figure  5 illustrated smear positive PTB prevalence prediction map (1 × 1 km spatial resolution) and prediction standard error map (1 × 1 km spatial resolution) according to the best geostatistical method.

Figure  6 illustrated Mycobacterium positive PTB prevalence prediction map (1 × 1 km spatial resolution) and prediction standard error map (1 × 1 km spatial resolution) according to the best geostatistical method.

As the resulting HIV prevalence prediction relates to a population for whom we generally never get to observe true HIV status, it is important to independently validate the model.

Therefore, we chose the 2 Kms as the distance between two center points for NTD rate prediction purposes; the corresponding ARV was 0.5347, which is an acceptable level reflecting the overall uncertainty of prevalence rate prediction (Fig. 3).