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Abstract Background Measles remains a major public health burden worldwide. Parents often hesitate to vaccinate children with chronic diseases. We investigated the association between the percentage of vaccination and chronic diseases and explore hospital infections’ role in the 2017–2019 measles outbreak across northern Vietnam provinces. Methods A total of 2,064 children aged 0–15 years old admitted for measles to the National Children’s Hospital during the outbreak were included in the study. Demographic information, clinical characteristics, vaccination statuses and laboratory examination were extracted from electronic medical records, vaccination records, or interviews with parents when other sources were unavailable. Results The incidence rate that provincial hospitals sent to the National Children’s Hospital was proportional to the population density of their provinces of residence. Early nosocomial transmission of measles was observed before community-acquired cases emerged in many provinces. Among patients aged over 18 months, those with chronic diseases had a proportion of vaccination of 9.4%, lower than patients without chronic diseases at 32.4%. Unvaccinated patients had a higher proportion of hospital-acquired infections with aOR = 2.42 (1.65–3.65), p

Anthrax, a widespread zoonosis in low and middle-income countries with low disease awareness and insufficient livestock vaccination coverage, has been known in Lao Cai Province in northern Vietnam for years before its apparent absence in 2009, which requires investigation as this infection is frequently reported from neighbouring provinces and countries. We aimed to describe the seasonal patterns of anthrax (1991-2008), compare livestock anthrax vaccine coverage to disease occurrence (1991- 2022), and delineate the high-risk areas to inform local disease surveillance in the province. We illustrated the seasonal pattern of anthrax and provided a comparison between livestock vaccine coverage and disease occurrence by purely spatial SaTScan (Poisson model, 25% population at risk) to detect spatial clusters of human and livestock anthrax using population derived from zonal statistics routines. The number of cases, crude cumulative incidence, and spatial clusters of human and livestock anthrax were mapped in QGIS. Results indicate peak anthrax incidence from May to October. Buffalo, domestic cattle, and horses accounted for 75% of total animal cases. Horse anthrax was more common in Lao Cai than in its neighbours and often occurred in years with human mortality. Vaccination covered less than 30% of the livestock population. We found an apparent pattern where anthrax was controlled from 1998-2003 with higher vaccine coverage (>20%) and identified spatial clusters of human and livestock anthrax in Muong Khuong, Bao Thang, and Bac Ha districts of Lao Cai. The local public health and veterinary agencies are recommended to revisit the high-risk areas and communicate with neighbouring provinces for a regional approach to anthrax surveillance and control.

The spread of infectious diseases from person to person is determined by the frequency and nature of contacts between infected and susceptible members of the population. Although there is a long history of using mathematical models to understand these transmission dynamics, there are still remarkably little empirical data on contact behaviors with which to parameterize these models. Even starker is the almost complete absence of data from developing countries. We sought to address this knowledge gap by conducting a household based social contact diary in rural Vietnam.A diary based survey of social contact patterns was conducted in a household-structured community cohort in North Vietnam in 2007. We used generalized estimating equations to model the number of contacts while taking into account the household sampling design, and used weighting to balance the household size and age distribution towards the Vietnamese population. We recorded 6675 contacts from 865 participants in 264 different households and found that mixing patterns were assortative by age but were more homogenous than observed in a recent European study. We also observed that physical contacts were more concentrated in the home setting in Vietnam than in Europe but the overall level of physical contact was lower. A model of individual versus household vaccination strategies revealed no difference between strategies in the impact on R(0).This work is the first to estimate contact patterns relevant to the spread of infections transmitted from person to person by non-sexual routes in a developing country setting. The results show interesting similarities and differences from European data and demonstrate the importance of context specific data.

Abstract BackgroundThe COVID-19 pandemic has revealed significant challenges in disease forecasting and in developing a public health response, emphasizing the need to manage missing data from various sources in making accurate forecasts. ObjectiveWe aimed to show how handling missing data can affect estimates of the COVID-19 incidence rate (CIR) in different pandemic situations. MethodsThis study used data from the COVID-19/SARS-CoV-2 surveillance system at the National Institute of Hygiene and Epidemiology, Vietnam. We separated the available data set into 3 distinct periods: zero COVID-19, transition, and new normal. We randomly removed 5% to 30% of data that were missing completely at random, with a break of 5% at each time point in the variable daily caseload of COVID-19. We selected 7 analytical methods to assess the effects of handling missing data and calculated statistical and epidemiological indices to measure the effectiveness of each method. ResultsOur study examined missing data imputation performance across 3 study time periods: zero COVID-19 (n=3149), transition (n=1290), and new normal (n=9288). Imputation analyses showed that K-nearest neighbor (KNN) had the lowest mean absolute percentage change (APC) in CIR across the range (5% to 30%) of missing data. For instance, with 15% missing data, KNN resulted in 10.6%, 10.6%, and 9.7% average bias across the zero COVID-19, transition, and new normal periods, compared to 39.9%, 51.9%, and 289.7% with the maximum likelihood method. The autoregressive integrated moving average model showed the greatest mean APC in the mean number of confirmed cases of COVID-19 during each COVID-19 containment cycle (CCC) when we imputed the missing data in the zero COVID-19 period, rising from 226.3% at the 5% missing level to 6955.7% at the 30% missing level. Imputing missing data with median imputation methods had the lowest bias in the average number of confirmed cases in each CCC at all levels of missing data. In detail, in the 20% missing scenario, while median imputation had an average bias of 16.3% for confirmed cases in each CCC, which was lower than the KNN figure, maximum likelihood imputation showed a bias on average of 92.4% for confirmed cases in each CCC, which was the highest figure. During the new normal period in the 25% and 30% missing data scenarios, KNN imputation had average biases for CIR and confirmed cases in each CCC ranging from 21% to 32% for both, while maximum likelihood and moving average imputation showed biases on average above 250% for both CIR and confirmed cases in each CCC. ConclusionsOur study emphasizes the importance of understanding that the specific imputation method used by investigators should be tailored to the specific epidemiological context and data collection environment to ensure reliable estimates of the CIR.

Introduction: Dengue fever (DF) in Vietnam remains a serious emerging arboviral disease, which generates significant concerns among international health authorities. Incidence rates of DF have increased significantly during the last few years in many provinces and cities, especially Hanoi. The purpose of this study was to detect DF hot spots and identify the disease dynamics dispersion of DF over the period between 2004 and 2009 in Hanoi, Vietnam., Methods: Daily data on DF cases and population data for each postcode area of Hanoi between January 1998 and December 2009 were obtained from the Hanoi Center for Preventive Health and the General Statistic Office of Vietnam. Moran's I statistic was used to assess the spatial autocorrelation of reported DF. Spatial scan statistics and logistic regression were used to identify space-time clusters and dispersion of DF., Results: The study revealed a clear trend of geographic expansion of DF transmission in Hanoi through the study periods (OR 1.17, 95% CI 1.02-1.34). The spatial scan statistics showed that 6/14 (42.9%) districts in Hanoi had significant cluster patterns, which lasted 29 days and were limited to a radius of 1,000 m. The study also demonstrated that most DF cases occurred between June and November, during which the rainfall and temperatures are highest., Conclusions: There is evidence for the existence of statistically significant clusters of DF in Hanoi, and that the geographical distribution of DF has expanded over recent years. This finding provides a foundation for further investigation into the social and environmental factors responsible for changing disease patterns, and provides data to inform program planning for DF control.