| Literature DB >> 25519710 |
Emma Diggle, Ramin Asgary, Georgia Gore-Langton, Erupe Nahashon, James Mungai, Rebecca Harrison, Abdullahi Abagira, Katie Eves, Zoya Grigoryan, David Soti, Elizabeth Juma, Richard Allan1.
Abstract
BACKGROUND: Conventional diagnosis of malaria has relied upon either clinical diagnosis or microscopic examination of peripheral blood smears. These methods, if not carried out exactly, easily result in the over- or under-diagnosis of malaria. The reliability and accuracy of malaria RDTs, even in extremely challenging health care settings, have made them a staple in malaria control programmes. Using the setting of a pilot introduction of malaria RDTs in Greater Garissa, North Eastern Province, Kenya, this study aims to identify and understand perceptions regarding malaria diagnosis, with a particular focus on RDTs, and treatment among community members and health care workers (HCWs).Entities:
Mesh:
Year: 2014 PMID: 25519710 PMCID: PMC4300559 DOI: 10.1186/1475-2875-13-502
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Figure 1The total numbers of malaria cases and numbers of artemether lumefantrine treatments distributed. Total number of AL treatments dispensed, confirmed malaria cases (microscopy and RDT), microscopy confirmed cases, and RDT confirmed cases across the study area between 2010 and 2013 and broken down in to yearly quarters (except 2010 data which was only collected over the period between September and December).
Figure 2Map of the study area. A map of the study area of Greater Garissa, North Eastern Province, Kenya [30].
Data collection methods and participants involved
| Data collection method (n) | Participants (n) |
|---|---|
| FGD (1) | HCWs (8) |
| FGD (34) | Patients (157) |
| IDI (23) | HCWs (23) |
| KI interviews (27) | CHWs, medical providers, religious figures, community leaders (27) |
Summary information of the data collection methods used and the numbers and types of participants involved.
Demographics of health care workers and key community informants
| Health care workers | No. | % (Total = 23) | Key informants | No. | % (Total = 27) |
|---|---|---|---|---|---|
|
| |||||
| Clinical officer | 4 | 17.4 | Cultural Leaders (Imam and Village Elder) | 3 | 11.1 |
| Nurse | 9 | 39.1 | Group Leaders (youth, women’s group, community information officer, prison leader, school teacher, college student) | 10 | 37.0 |
| Laboratory technician | 9 | 39.1 | Administrative Health Key Informants (Chairman Health Centre, Hospital Committee Member) | 3 | 11.1 |
| Pharmacist | 1 | 4.3 | Other health worker (community health workers) | 6 | 22.2 |
| Service industry (business man, tea vendor, private pharmacy owner, chairman water project) | 5 | 18.5 | |||
|
| |||||
| 30 and under | 15 | 65.2 | 30 and under | 13 | 48.1 |
| 31-41 | 8 | 34.8 | 31-41 | 10 | 37.0 |
| 42-51 | 0 | 0 | 42-51 | 3 | 11.1 |
|
| |||||
| Somali | 1 | 4.3 | Somali | 20 | 74.0 |
| Other | 20 | 87.0 | Other | 6 | 22.2 |
| Unknown | 2 | 8.7 | Unknown | 1 | 3.7 |
|
| |||||
| Female | 8 | 34.8 | Female | 7 | 25.9 |
| Male | 15 | 65.2 | Male | 20 | 74.0 |
|
|
| ||||
| 3 years and above | 23 | 100 | Illiterate | 4 | 14.8 |
| Fewer than 3 years | 0 | 0 | Primary School dropout | 7 | 25.9 |
| Primary School complete | 3 | 11.1 | |||
| Secondary School dropout | 7 | 25.9 | |||
| Secondary School Leaver | 4 | 14.8 | |||
| Diploma | 1 | 3.7 | |||
| Unknown | 1 | 3.7 | |||
Demographic information, including the profession, age, ethnicity/tribe, gender, and years of professional training, separated for health care workers and key informants.