Click to expand Are you sure it wasn't DHSS? People are so cheap when they place a classified advertisement that they end up inventing new abbreviations just so they don't have to pay for an extra line. Even native speakers have trouble getting their head around what is being referred to. I can't help in this case, just a passing comment.
Although I did wonder if it meant people on an unemployment benefit as the advertisement states that they are looking for working people or students. Thank you for helping me It's funny: it was a free ad on a forum. But I agree They don't mean anything to me, but I suppose you're right and this girl is looking for someone who can pay the rent.
I agree with loladamore, it definitely means "DHSS" and yep, it's basically just a way of saying they don't want unemployed people, etc Haven't seen this before, but, maybe That is, devotees of the band the Grateful Dead, or, by extension, all kinds of freaky people who might frighten your Aunt Elsa if she came to visit.
English-Ireland top end. Search This Site. Division of Social Services. Attention: Claymont State Service Center will be temporarily closed.
All calls will be temporarily redirected to another building and most staff will be relocated to the Northeast State Service Center. Learn More. Download here for FREE today! Descarga aqui gratis hoy. Change to the U. General Assistance A state-funded program designed to provide cash assistance to low-income people who do not qualify for federally funded programs, such as TANF or Social Security benefits. Child Care This service provides support for families with children to enable the caretaker to hold a job, obtain training or meet special needs of the parent or child.
Refugee Cash Assistance National voluntary agencies volags place refugees with local sponsors throughout the United States inlcuding the State of Delaware. Medicaid The Division of Social Services provides six main types of medical assistance services.
Health Insurance Learn how Delaware is working to make health care better. Applications Determine if your household is potentially eligible for Delaware's Social Service Programs and download an application today. Preventing Medicare Fraud Empowering seniors to prevent healthcare fraud. Data from the Butajira DSS — and the Ethiopia DHS rounds for and formed the basis of comparative analyses of mortality rates among those aged under 20 years, using Poisson regression models for adjusted rate ratios.
DSS data were more susceptible to local epidemic variations, while DHS data tended to smooth out local variation, and be more subject to recall bias. Both DSS and DHS approaches to mortality surveillance gave similar overall results, but both showed method-dependent advantages and disadvantages.
In many settings, this kind of joint-source data analysis could offer significant added value to results. Peer Review reports. The acute shortage of reliable population-based health data in the world's poorer countries, where complete and compulsory registration of vital events and other health data is currently impracticable or unaffordable, have led to other strategies for obtaining at least some data. A number of DSSs have been established, mainly across Africa and Asia, the majority of which are affiliated to the Indepth Network [ 1 ].
Although there are local and contextual variations in the design of individual DSSs, which generally operate autonomously, the basic concept involves the identification of a geographically defined population, typically of 30 to thousand people. An initial census of the defined population forms the basis for an open cohort that can be followed longitudinally. New individuals can enter the cohort by birth or in-migration, while cohort members can exit by out-migration or death.
Alongside surveillance of vital events birth, migration and death , other health-relevant parameters such as household characteristics, individual characteristics and experiences of health and disease are routinely collected.
Established DSSs can also offer unique opportunities as platforms for interventions, such as vaccine trials. The DHS programme is a global U. Government-backed initiative to undertake relatively large and complex cross-sectional surveys of demographic and health parameters on nationally representative samples in poorer and middle-income countries [ 2 ].
The underlying methodology for this has been standardised, apart from small details relating to country-specific requirements, and both reports and datasets from particular DHS rounds are made available via the internet. Nationally distributed cluster samples of households are taken as the basis for a DHS round. DHSs are repeated at approximately 5-year intervals in many countries around the world, with each round drawing a fresh cross-sectional sample. This district was purposefully chosen as being potentially representative for a DSS in , on the basis of being at least km from any major city, but not in a peripheral border region; combining a mixture of the highland and lowland environments typical of Ethiopia; and containing a mixture of ethnic and religious groups.
National DHS sample surveys have been undertaken in Ethiopia in and The aim of this paper is to review child and adolescent mortality outputs from both the BRHP DSS and the Ethiopian DHS data from the and rounds, comparing findings within areas of common ground in an attempt to see how the two different approaches complement and speak to each other. All of the households have since been visited regularly to record vital events births, deaths, in and out migrations and the dataset describing this dynamic cohort up to 31 st December was used for this analysis.
By this time the resident population had grown to 54, [ 3 ]. A total of 68, individuals were included, each contributing an average of 6. Deaths were recorded for 6, individuals. The DHS and datasets for Ethiopia both included detailed birth histories taken from women in the household sample, which included date of birth for ever-born children and date of death for those no longer alive at the time of interview.
In , interviews were completed for 15, women aged 15 to 49 years, and in 14, women were interviewed [ 4 , 5 ]. The date when women took up residence in their current household was recorded, as well as the interview date. Thus it was possible to construct a pseudo-cohort dataset with a record for each child, covering the same period to and same age range 0 to 19 years as the BRHP dataset. Individual child records from the and DHS surveys were allowed to overlap in time, given that the two samples were drawn independently.
Person-time for each child started at the latest of: 1 st January , date of birth or date of mother's residence starting. Person-time ended at the earliest of: date of death, date of interview, twentieth birthday or 31 st December A total of 75, children were included, each contributing an average of 7. Deaths were recorded for 10, individuals. Both the DSS and DHS datasets were incorporated into Poisson regression models using Stata software in which individual person-time was the exposure variable and death the outcome measure.
The BRHP DSS dataset included 6, deaths among , person-years in the age range 0 to 19 years during the period to , a crude mortality rate of The corresponding national DHS dataset included 10, deaths among , person-years, a crude rate of Within these national data, the subset for SNNPR amounted to 1, deaths in 84, person-years, a crude rate of Table 1 shows a breakdown of deaths and person-time by age group, sex, residence, year and region for both DSS and DHS data.
One cannot exclude the possibility that these similarities are entirely coincidental, but, given the purposeful initial selection of Butajira as a district that could be nationally representative, such coincidence is unlikely. Nevertheless, Table 2 reveals many small but statistically significant differences, made possible as a result of the relatively large overall samples.
It is clear that urban or rural residence is an important factor for child mortality, although it is not always a concept that is easy to define. In the BRHP DSS, the "urban" population is one of the four administrative units within Butajira town — and, although this is far from being a large, sophisticated city, the benefits of living in the town compared with adjacent villages have been consistently clear in many analyses from the BRHP DSS [ 3 , 7 ].
It is also clear from the DHS data that urban residence is advantageous — the Addis Ababa region has the lowest regional figures, and in the overall sample urban residents experience significantly lower mortality.
The DHS sample was based on census enumeration areas from the national census and each of these areas was officially designated as either urban or rural.
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