BMC Public Health 2005, 5:58 http://www.biomedcentral.com/1471-2458/5/58 the study community and reported without any reserva- tion, especially for adults. The recall period however can affect the quality of detailed information collected for VA use. Baqui utilized a five year recall period for children in Bangladesh and reported that increase recall lapse has no clear adverse effect on data quality [24]. In addition, the questions on events surrounding mortality in this study are very simple and direct. For example, one of the ques- tions was on duration of illness in general, not on dura- tion of specific symptoms. The omission of very specific questions was helpful in minimizing the problem of recall. The major problem associated with the long time span was the unavailability of relatives of the deceased for interview, due to out migration or other reasons. There was a marked decline in the proportion of the missed cases from 1995 to 1999. The high number of missed cases for the deaths during "01/01/95"-"08/31/97" may have affected the results of this study and can be sighted as one of the limitations encountered. This indicates that VA information need to be gathered closer to the event, i.e. within a time span of not more than two years. The simplified algorithm used for diagnosis of cause of death classified illnesses into "broad" categories consisting of 12 causes of death. For example all acute febrile illnesses and all forms of tuberculosis were lumped into one category. Although this "broad" classification has the disadvantage of diagnosing only a limited variety of diseases and leav- ing out some diseases as undetermined, it makes easier the use of VA and the algorithm in many similar settings once validated. Other studies have demonstrated that simplicity of the questionnaire, the use of lay interviewers, lack of complexity in the algorithm used, and the broad categories of diseases increase the validity of a study and its reproducibility in other settings [6]. Although a validation study was not done on the "expert algorithm" used, the combinations of symptoms and duration of illness used for diagnosing injuries, maternal deaths, acute febrile illnesses, and meningitis are believed to be highly sensitive but not very specific. For example the algorithm of AFI has the combination of "duration of illness less than 15 days", "fever" and "headache". This combination can pick almost all deaths due to AFIs, but it increases the false positivist. The algorithm used for tuberculosis, AIDS, liver diseases, and pneumonia are less sensitive but more specific than the previously stated diseases categories, because of the sign and symptom combinations used. A validation study for verbal autopsy in adults had shown that the cause spe- cific mortality fraction obtained using "expert algorithms" was within ± 20% of the gold standard for malaria, men- ingitis, tuberculosis/AIDS, acute abdomen conditions, diarrheal diseases, direct maternal causes, chronic liver diseases and renal disorders [14]. The algorithm used for cardiovascular diseases and chronic obstructive pulmonary diseases may not have per- formed well because of the unstable nature of the diseases resulting in difficulty of sighting symptoms specific to them [7]. The "expert algorithm" used in this study may not have given the correct diagnosis for some of the dis- eases at the individual level. However, in the face of absence of information on causes of mortality in Ethiopia, the information generated at the population level using these combinations is very useful in identifying priority health problems that need urgent intervention in rural populations. Causes of death diagnosed through the expert algorithm showed that one fourth of the deaths were due to acute febrile illnesses. The proportion was much higher in the rural areas than in the town. In contrast, HIV/AIDS accounted for a higher proportion in the town than the rural areas. A previous study in the same area has shown a similar pattern of disease occurrence [16]. We have tried to see if there is any inconsistency in the causes of death as a result of the greater number of missed cases in the first one and half year of the study period. The deaths during the later period of the study have very sim- ilar pattern when compared to the total five year deaths. For communicable diseases it was 60.8% vs. 59.2%, for non-communicable 24.1% vs. 25.4% and for maternal causes 7% vs. 6.9%. This consistency can be taken as an indicator of non-differential loss of cases over the speci- fied period of time. This also indicate the robustness of the approach even when data are not complete, which is truly the case in most rural settings of developing countries. This study has grossly indicated the magnitude of female deaths due to maternal causes, which is very difficult to come by as measuring maternal mortality ratio is very expensive [25-27], such information could be helpful to implement practical interventions locally. Considerations in the line of using the probabilistic approach to interpret- ing verbal autopsies described by Byass might help to fur- ther simplify the methodology and facilitate its application in large surveys [28]. However, it is important to note that the questionnaire in this study was tailored to yield maximum information from mostly illiterate and rural people as administered by lay interviewers. Hence its applicability might be limited to situations similar to the study area both in terms of availability of information and profile of health problems, which is dominated by com- municable diseases. Conclusion In conclusion, this study provides evidence that interview- ing deceased relatives using a simplified VA questionnaire Page 6 of 7 (page number not for citation purposes)