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Background. This study assesses the prevalence of Vietnamese children receiving the hepatitis B (HepB) vaccine birth dose and explores its associated socioeconomic factors. Methods. We used the data of the Multiple Indicator Cluster Survey, 2014. We estimated the overall percentage of HepB birth dose vaccination among 0–23-month-old children and its percentages according to selected characteristics. Multiple logistic regression was applied. Results. 62.8% of children received the HepB vaccine birth dose. The prevalence rates by selected factors ranged from 35.3% to 76.7%. The categories with the lowest prevalence rates were children who had low birth weight (41.6%), had a mother aged less than 20 years (35.3%), had a mother with primary or less education (42.7%), belonged to ethnic minorities (30.3%), resided in rural areas (59.9%), and were in the 1st quintile of mother’s socioeconomic status (38.6%). Receiving HepB vaccine birth dose was associated with child’s birth weight, mother’s age, mother’s education, socioeconomic status, and ethnicity. Conclusions. This study identified vulnerable groups, upon which policy-makers should focus their efforts to equitably and sustainably tackle birth dose HepB vaccine coverage as well as the full vaccination coverage, thereby promoting long-lasting herd immunity in this country.

In this paper a rainfall threshold and a Bayesian probability model are presented for the landslide occurrence of shallow landslides in Ha Giang city and the surroundings, Vietnam. The model requires the data on daily rainfall combined with the actual dates of landslide occurrences. Careful study on the database is a prerequisite for the paper. For this reason, selecting the input data was carried out carefully to ensure the reliable results of the study. The daily rainfall data covering a time span of 57 years was collected from a unique rain gauge station of National Centre for Hydro-meteorological Forecasting of Vietnam (from 1957 to 2013) and a landslide database with some landslides (37 of total of 245 landslides) that containing dates of occurrence, was prepared from historical records for the period 1989 to 2013. Rainfall thresholds were generated for the study area based on the relationship between daily and antecedent rainfall of the landslide events. The results shows that 3-day antecedent rainfall (with the rainfall threshold was established: R T = 40.8 − 0.201R 3ad) gives the best fit for the existing landslides in the landslide database. The Bayesian probability model for one-dimensional case was established based on 26 landslides for the period 1989 to 2009, daily rainfall data with the same time and the values of probability varies from 0.03 to 0.44. Next, the Bayesian probability model for two-dimensional case was generated based on 11 landslides, rainfall intensity and duration in three months (May, June and July) of 2013 and the values of probability ranges from 0.08 to 0.67, and computed values of conditional landslide probability P(A|B) from two-dimensional case of Bayesian approach are clearly controlled by rainfall intensity > 40 mm with rainfall duration > 0.3 day. How to cite this paper: Do, H.M. and Yin, K.L.

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