War and Health Care Services Utilization for Chronic Diseases in Rural and Semiurban Areas of Tigray, Ethiopia.

Importance: The war in Tigray, Ethiopia, has disrupted the health care system of the region. However, its association with health care services disruption for chronic diseases has not been well documented.

Objective: To assess the association of the war with the utilization of health care services for patients with chronic diseases.

Trends in malaria cases, hospital admissions and deaths following scale-up of anti-malarial interventions, 2000-2010, Rwanda.

Background: To control malaria, the Rwandan government and its partners distributed insecticide-treated nets (ITN) and made artemisinin-based combination therapy (ACT) widely available from 2005 onwards. The impact of these interventions on malaria cases, admissions and deaths was assessed using data from district hospitals and household surveys.

Methods: District records of ITN and ACT distribution were reviewed.

Reductions in malaria and anaemia case and death burden at hospitals following scale-up of malaria control in Zanzibar, 1999-2008.

Background: In Zanzibar, the Ministry of Health and partners accelerated malaria control from September 2003 onwards. The impact of the scale-up of insecticide-treated nets (ITN), indoor-residual spraying (IRS) and artemisinin-combination therapy (ACT) combined on malaria burden was assessed at six out of seven in-patient health facilities.

Methods: Numbers of outpatient and inpatient cases and deaths were compared between 2008 and the pre-intervention period 1999-2003.

Estimating trends in the burden of malaria at country level.

National disease burdens are often not estimated at all or are estimated using inaccurate methods, partly because the data sources for assessing disease burden-nationally representative household surveys, demographic surveillance sites, and routine health information systems-each have their limitations. An important step forward would be a more consistent quantification of the population at risk of malaria. This is most likely to be achieved by delimiting the geographical distribution of malaria transmission using routinely collected data on confirmed cases of disease.