Parasitological confirmation of malaria prior to treatment is recommended for patients of all ages, with malaria rapid diagnostic tests (mRDTs) an important tool to target artemisinin-based combination therapies (ACTs) to patients with malaria. To evaluate the impact on case management practices of routine government implementation of mRDTs, we conducted large-scale health facility surveys in three regions of Tanzania before and after mRDT roll-out.
Febrile patients at randomly selected health facilities were interviewed about care received at the facility, and blood samples were collected for reference blood smears. Health facility staff were interviewed about their qualifications and availability of malaria diagnostics and drugs.
The percentage of febrile patients tested for malaria at the facility increased from 15.8% in 2010 to 54.9% in 2012. ACTs were obtained by 65.8% of patients positive by reference blood smear in 2010 and by 50.2% in 2012 (
Roll-out of mRDTs in Tanzania dramatically improved diagnostic testing for malaria and reduced overuse of ACTs for patients without parasitemia. However, post–roll-out almost 50% of febrile patients did not receive a diagnostic test, and almost 50% of patients testing positive did not receive ACTs. Stock-outs of ACTs and mRDTs were important problems. Further investigation is needed to determine reasons for not providing ACTs to patients with malaria and potential for inappropriate antibiotic use.
Artemisinin-based combination therapies (ACTs) are the first-line drugs for malaria in most endemic countries, but there are concerns that targeting of ACTs to those in need remains poor. Many patients with malaria do not obtain ACTs, while many others with febrile illness obtain ACTs but do not have malaria parasitaemia (
Malaria rapid diagnostic test implementation has had a varied impact on clinical decisions. While some studies have demonstrated significant reductions in the proportion of patients obtaining an antimalarial drug (
Artemether–lumefantrine (ALu) has been the first-line drug for treatment of malaria in Tanzania since 2004, although roll-out to the public sector did not begin until 2006. Treatment at government hospitals, health centres and dispensaries is intended to be free of charge for children below 5 years old and pregnant women, although this policy is not always adhered to (
While mRDT implementation has been studied in many settings, very few studies have reported evaluations of mRDT roll-out under routine operational conditions, where implementation has been purely the responsibility of the government (
In this article, we report the impact on case management practices of routine government implementation of provision and use of mRDTs in Tanzania, based on large-scale health facility surveys conducted before and after mRDT roll-out. The surveys were conducted in three of mainland Tanzania's 21 regions, reflecting the country's diversity of malaria epidemiology and commodity availability, thereby allowing us to explore the impact of policy implementation under a range of contexts.
This study was part of the IMPACT2 project, which took place in Mwanza, Mbeya and Mtwara regions of Tanzania, with populations of approximately 3 771 000, 2 822 000 and 1 375 000, respectively (National Bureau of Statistics
Roll-out of mRDTs took place in February 2011 in Mwanza and Mbeya, but not until May 2012 in Mtwara. A limited number of facilities in Mwanza and Mtwara had participated in small-scale mRDT pilots prior to roll-out. Roll-out involved training for 1 week of regional representatives and four representatives from each district, who then in turn trained one or two health workers from each public facility, usually the incharge clinician and laboratory technician or another health worker. The mRDT-specific training built upon earlier trainings on case management of malaria with ACTs, some of which had previously included instruction on performing mRDTs. Content included the rationale for using mRDTs, the mRDT algorithm for case management, reporting procedures for monitoring of mRDT use and the importance of compliance to test results. The trainings included demonstrations and practical exercises on performing mRDTs and reading results. Health workers receiving formal training were expected to pass on the information to colleagues who had not attended in a cascade-training approach. An initial stock of mRDTs was supplied to each facility, after which additional mRDTs could be ordered based on reported consumption.
Baseline health facility surveys took place in 2010, during May–June in Mwanza, July–August in Mbeya and September–October in Mtwara. Post-implementation surveys followed in 2012 in Mwanza in April–May, Mbeya in May–June and Mtwara in June–July (Figure
Timing of surveys and malaria rapid diagnostic test rollout.
The sample size for the study was calculated to detect a 15% absolute change in a composite indicator of appropriate treatment given true malaria parasitaemia status, as identified by reference blood smears collected by study staff. The composite indicator was defined as the proportion of patients with fever or history of fever who had a malaria-positive reference blood smear and received ACT at the health facility, or had a malaria-negative reference blood smear and did not receive any antimalarial. Assuming 5% significance, 80% power, a baseline proportion receiving appropriate treatment of 65%, 5% refusal and a design effect of 2.5, 338 patients with fever or history of fever per study region were required in each survey round.
In each region, 35 health facilities in 2010 and 60 in 2012 were randomly selected with probability proportional to malaria outpatient utilisation, based on the most recent data available for all government health facilities. Due to slower than expected recruitment in 2010, additional facilities were added from a list of randomly selected alternates for each region, and the total number of facilities selected in 2012 was increased. A similar number of patients were sampled at each facility, resulting in an approximately self-weighting survey sample. Each facility was visited by the study team for 1 day. Patients presenting for outpatient care on the day of the study team's visit with fever or history of fever in the previous 48 hours were enrolled upon arrival at the health facility, subject to informed consent having been obtained. To achieve sufficient sample size, facilities were replaced with randomly selected alternate facilities of similar size if no eligible patients attended the facility on the day of the study team's visit. In 2010, the first 12 eligible patients under five and the first 12 eligible patients aged five and above were enrolled. Because this target was not met at most facilities in 2010 and additional randomly selected facilities had to be added, the protocol was adjusted in 2012 to enrol all patients meeting eligibility criteria at each facility during daytime operating hours.
After completion of their consultations with facility staff, patients were interviewed by research staff about demographic information, previous treatment for fever and care received at the facility, including blood tests for malaria conducted as part of the consultation (facility tests) and drugs obtained. Health facility staff seeing enrolled patients were interviewed about their qualifications, training, knowledge, and availability of antimalarial drugs, mRDTs, microscopy and antibiotics.
Facilities were considered to have mRDTs in stock if the study team observed at least one full box containing 25 non-expired mRDTs, and facilities were considered to have microscopy upon observation of a functional microscope, slides and Giemsa stain for at least 25 smears, and a microscopist. Facilities were considered to have ALu in stock if they had had at least one observed, non-expired blister pack for any age/weight group. Antibiotics were considered to be in stock if any non-expired oral antibiotics were observed.
Finger prick blood samples were taken from enrolled patients by study staff to test for malaria parasitaemia by study mRDTs (ICT Diagnostics, Cape Town, South Africa) and thick blood smears (reference blood smears) stained with 10% Giemsa. Reference blood smears were double-read at the Ifakara Health Institute in Bagamoyo by two microscopists blinded to the initial reading and patients' study mRDT results, with discrepant readings read by a third microscopist. Parasites were counted against 200 white blood cells, and slides were considered negative if no parasites were found after examining 100 fields.
All questionnaires and consent forms were translated into Swahili and piloted by native speakers. The study protocol was approved by the ethical review boards of the Ifakara Health Institute and the London School of Hygiene and Tropical Medicine. CDC investigators provided technical assistance in design and analysis but were not engaged in data collection. Written informed consent was obtained from health workers and patients or their caregivers prior to enrolment. Patients who tested positive by the study mRDT and had not already received ACT were given the weight-appropriate blister pack by study staff. Pregnant women in the first trimester and children below 5 kg who tested positive were referred back to the health facility incharge for treatment decisions.
Data were collected using personal digital assistants (PDAs) and were analysed in Stata 11.0 (Stata Corporation, College Station, USA) using survey commands to account for the two-stage survey design with stratification by region. Percentages with 95% confidence intervals and p-values for the Pearson design-based
We visited 140 health facilities (11 hospitals, 24 health centres and 105 dispensaries) between May and October 2010, and 176 health facilities (13 hospitals, 31 health centres, 132 dispensaries) between April and July 2012.
In 2010, only 3.3% of health facilities had mRDTs in stock, while 10.9% had microscopy and 11.8% had either mRDTs or microscopy available (Figure
Availability of malaria diagnostics, artemether–lumefantrine and oral antibiotics in health facilities in 2010 (pre-roll-out) and 2012 (post-roll-out).
We interviewed 154 health workers in 2010 and 209 in 2012. While most health worker characteristics remained similar between 2010 and 2012 (Table
Health worker characteristics (Percent, 95% Confidence interval)
| Health workers with interview data (N) | Mwanza | Mbeya | Mtwara | Total | ||||
|---|---|---|---|---|---|---|---|---|
| 2010 | 2012 | 2010 | 2012 | 2010 | 2012 | 2010 | 2012 | |
| 41 | 71 | 64 | 72 | 49 | 66 | 154 | 209 | |
| Age (years) | ||||||||
| 25-34 | 15.1 (5.2, 36.9) | 34.3 (23.7, 46.8) | 29.2 (14.7, 49.7) | 31.7 (19.9, 46.3) | 10.5 (4.2, 23.7) | 21.4 (10.9, 37.7) | 20.7 (12.6, 32.0) | 30.6 (23.6, 38.7) |
| 35-44 | 32.5 (17.9, 51.6) | 15.7 (8.4, 27.4) | 19.8 (9.6, 36.5) | 9.2 (4.1, 19.5) | 23.7 (11.4, 43.0) | 19.6 (10.1, 34.6) | 24.7 (16.6, 35.2) | 14.5 (9.8, 20.9) |
| 45 and older | 52.4 (34.4, 69.8) | 50.0 (37.4, 62.5) | 51.0 (30.2, 71.3) | 59.1 (45.0, 71.9) | 65.8 (46.4, 81.1) | 59.0 (42.2, 73.9) | 54.7 (42.4, 66.4) | 55.1 (47.4, 62.6) |
| Male sex | 71.3 (51.9, 85.1) | 65.8 (54.4, 75.6) | 47.5 (27.6, 68.2) | 49.3 (34.9, 63.8) | 39.8 (23.3, 59.0) | 43.2 (26.9, 61.0) | 53.4 (40.8, 65.6) | 52.9 (45.2, 60.4) |
| Qualifications | ||||||||
| Medical or Clinical Officer | 55.8 (37.4, 72.8) | 70.1 (55.9, 81.2) | 41.9 (24.1, 62.1) | 40.9 (27.5, 55.8) | 54.9 (33.8, 74.4) | 36.3 (22.9, 52.1) | 49.1 (37.0, 61.4) | 52.7 (43.3, 61.8) |
| Nurse, midwife or assistant clinical officer | 39.3 (22.9, 58.5) | 27.2 (16.8, 40.9) | 28.7 (14.6, 48.4) | 46.8 (32.5, 61.7) | 36.5 (17.6, 60.7) | 50.5 (34.0, 66.9) | 33.7 (23.3, 46.1) | 39.0 (30.4, 48.4) |
| Assistant or attendant | 4.9 (1.0, 20.7) | 2.7 (0.7, 9.9) | 29.5 (10.6, 59.7) | 12.3 (6.1, 23.0) | 8.6 (3.0, 22.2) | 13.2 (6.1, 26.3) | 17.1 (7.1, 36.0) | 8.3 (5.2, 13.1) |
| Number of patients seen on a regular day | ||||||||
| 15 or less | 27.0 (13.7, 46.2) | 29.7 (17.9, 45.0) | 70.9 (54.0, 83.5) | 49.9 (35.5, 64.2) | 31.3 (16.8, 50.6) | 23.3 (12.8, 38.8) | 48.3 (36.4, 60.5) | 34.8 (26.6, 43.9) |
| 16-30 | 50.5 (32.7, 68.1) | 53.6 (40.2, 66.5) | 25.3 (14.1, 41.2) | 38.3 (25.6, 52.9) | 63.2 (43.6, 79.2) | 64.0 (47.8, 77.5) | 41.6 (30.7, 53.3) | 51.1 (42.7, 59.5) |
| More than 30 | 22.5 (11.5, 39.6) | 16.7 (6.6, 36.2) | 3.8 (1.6, 8.9) | 11.8 (5.8, 22.6) | 5.6 (1.5, 18.9) | 12.7 (6.0, 24.8) | 10.1 (6.0, 16.6) | 14.1 (8.3, 23.2) |
| Attended formal training on ACTs in the last 5 years | 70.3 (51.4, 84.2) | 47.3 (34.7, 60.2) | 40.2 (23.2, 60.0) | 61.1 (47.1, 73.4) | 77.1 (60.9, 88.0) | 73.6 (55.1, 86.3) | 57.8 (44.6, 70.0) | 58.0 (49.5, 66.0) |
| Attended formal training on how to use mRDTs in the last 5 years | 8.1 (2.3, 25.9) | 49.3 (33.6, 65.2) | 3.8 (0.7, 18.4) | 58.8 (44.5, 71.7) | 9.8 (3.6, 24.4) | 79.0 (60.0, 90.5) | 6.5 (3.0, 13.5) | 59.4 (49.4, 68.7) |
| Received supervision on ACTs in the last six months | 31.8 (17.5, 50.6) | 30.8 (20.0, 44.2) | 19.1 (9.8, 33.9) | 29.1 (18.0, 43.4) | 48.2 (29.1, 67.9) | 19.2 (10.1, 33.3) | 29.5 (20.9, 39.8) | 27.5 (20.7, 35.5) |
| Reported having ACT job aid in consultation room | 78.4 (59.3, 90.1) | 62.2 (49.3, 73.6) | 64.1 (37.7, 84,1) | 66.4 (52.5, 78.0) | 88.6 (74.2, 95.4) | 77.7 (63.3, 87.6) | 74.0 (58.0, 85.4) | 67.3 (59.5, 74.3) |
| Correctly identified correct dosage regimen of ACT for a 10 kg child | 65.9 (47.4, 80.6) | 92.7 (83.6, 96.9) | 81.9 (66.4, 91.2) | 92.0 (81.4, 96.8) | 87.1 (71.2, 94.8) | 90.9 (79.3, 96.3) | 77.9 (68.3, 85.3) | 92.0 (86.9, 95.2) |
| Correctly identified correct dosage regimen of ACT for an adult | 96.0 (75.7, 99.5) | 98.5 (89.5, 99.8) | 100.0 | 98.4 (89.4, 99.8) | 100.0 | 90.0 (63.6, 97.9) | 98.7 (91.2, 99.8) | 96.4 (89.2, 98.9) |
Includes formal training on ACTs where health workers were taught how to use mRDTs.
Of 1746 patients interviewed in 2010, 59.2% were under 5 years old, while in 2012, 66.2% of 1710 patients were under-fives (Table
Patient characteristics (Percent, 95% Confidence interval)
| Mwanza | Mbeya | Mtwara | Total | |||||
|---|---|---|---|---|---|---|---|---|
| 2010 | 2012 | 2010 | 2012 | 2010 | 2012 | 2010 | 2012 | |
| Patients with interview data ( | 689 | 750 | 559 | 388 | 498 | 572 | 1746 | 1710 |
| Percent below 5 years | 58.8 (51.4, 65.8) | 68.5 (63.0, 73.6) | 55.1 (48.1, 61.9) | 63.7 (58.0, 69.0) | 64.3 (58.5, 69.6) | 64.9 (59.7, 69.7) | 59.2 (55.1, 63.1) | 66.2 (63.0, 69.2) |
| Male sex | 43.4 (38.8, 48.1) | 43.6 (40.2,47.1) | 42.6 (38.0, 47.3) | 43.0 (38.6, 47.6) | 44.0 (40.4, 47.6) | 41.6 (37.6, 45.7) | 43.3 (40.8, 45.9) | 42.8 (40.6, 45.1) |
| Sought care at another source before coming to health facility | 30.8 (26.7, 35.2) | 38.4 (34.5, 42.5) | 10.6 (7.4, 14.9) | 30.2 (24.4, 36.6) | 11.5 (7.2, 17.7) | 25.9 (20.6, 31.9) | 18.8 (16.3, 21.5) | 32.4 (29.5, 35.4) |
| Can reach health facility within one hour | 69.1 (63.8, 74.0) | 72.4 (67.4, 76.9) | 74.8 (69.3, 79.6) | 69.7 (62.6, 76.0) | 68.5 (61.1, 75.0) | 65.1 (59.8, 70.1) | 70.8 (67.4, 74.0) | 69.3 (66.1, 72.3) |
| Slept under insecticide-treated net | 81.7 (77.5, 85.2) | 88.3 (85.1, 91.0) | 75.8 (71.7, 79.5) | 79.5 (74.8, 83.5) | 81.9 (77.4, 85.7) | 84.5 (80.8, 87.6) | 80.0 (77.5, 82.1) | 85.1 (83.0, 87.0) |
| Median days since fever onset | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| Percent testing positive by study mRDT | 21.3 (16.6, 26.9) | 14.4 (9.8, 20.8) | 5.9 (3.5, 9.9) | 6.5 (3.3, 12.1) | 37.0 (29.8, 44.7) | 45.1 (38.6, 51.8) | 20.8 (17.7, 24.4) | 22.9 (19.5, 26.7) |
| Percent testing positive by study blood smear | 6.6 (4.4, 9.8) | 10.7 (7.1, 15.7) | 1.6 (0.7, 3.5) | 4.8 (2.2, 10.0) | 20.9 (16.4, 26.3) | 31.8 (27.1, 36.8) | 9.2 (7.4, 11.4) | 16.5 (13.9, 19.4) |
A long-lasting insecticide-treated net (LLIN) obtained within the previous 3 years or a conventional net treated with insecticide in the previous year.
The results show a large increase in the use of malaria diagnostics post-implementation (Figure
Percent of patients receiving malaria diagnostic test at health facility pre and post malaria rapid diagnostic test roll-out.
We present results on treatment obtained firstly according to the facility test and secondly according to the reference blood smear. Results in relation to the facility test are presented for 2012 only, as few facility tests were conducted in 2010. As explained above, we define appropriate antimalarial treatment for patients with positive test results as obtaining an ACT and for those with negative results as not obtaining an antimalarial. Only three women in 2010 and three women in 2012 reported being in the first trimester of pregnancy and had a positive reference blood smear, and of these, only one in 2010 received any treatment (quinine). Due to their negligible numbers, these women were not excluded from the analysis.
In 2012, 56.5% of patients testing positive by the facility test obtained an ACT, while 7.7% of those testing negative and 23.6% of those not tested obtained any antimalarial (Figure
Treatment obtained at health facilities according to facility malaria test (microscopy or mRDT) post-roll-out (Percent, 95% CIs).
We assessed treatment obtained against reference blood smear results in 2010 and 2012 (Figure
Patients receiving correct treatment according to parasitaemia status by study blood smear pre and post mRDT roll-out.
As reported above for the facility tests, we also report appropriate treatment for patients with positive reference blood smears and negative reference blood smears separately. ACTs were obtained by 65.8% of patients testing positive in 2010 (denominator of
The consequences for overall levels of ACT and antibiotic treatment are shown in Figure
Patients receiving ACT and antibiotic by region pre and post mRDT roll-out.
We have presented results from large-scale health facility surveys in three regions of Tanzania before and after the roll-out of mRDTs in all levels of government health facilities. We have reported on the availability and use of diagnostic testing among febrile patients and case management with ACTs based on facility test results and reference blood smears, and we have also examined the effect of this policy change on prescription of antibiotics. The findings are representative of Mwanza, Mbeya and Mtwara Regions, which encompass considerable diversity in malaria transmission, economic status and culture.
Malaria rapid diagnostic test roll-out in Tanzania led to substantial changes in the provision of malaria case management in public facilities. Post-roll-out nearly 70% of facilities had mRDTs in stock and 60% of health workers had received formal mRDT training. This was associated with a large increase in the proportion of febrile outpatients tested for malaria from 15.5% in 2010 to 54.9% in 2012, and facility mRDT testing was shown to have relatively good sensitivity and specificity. However, there were still major gaps in diagnostic coverage, with almost half of all patients not tested. In Mtwara, the proportion of patients tested (71.5%) and the proportion of health workers with formal mRDT training (79.0%) were higher than in Mwanza and Mbeya, reflecting the more recent roll-out, and therefore, lower potential for training coverage to be eroded by staff turnover or for mRDT stock-outs to arise. The latter was an important factor in suboptimal diagnostic coverage, with the per cent tested increasing to 70% if only facilities with diagnostics available were considered. Other studies have similarly reported less-than-optimal coverage of diagnostic tests (
Provider compliance with test results in terms of prescription has been a major concern in the roll-out of improved services for parasitological confirmation. Reported reasons for low compliance include providers' or patients' lack of confidence in the test result, the presence of symptoms associated with malaria, and the lack of alternative diagnoses identified by the providers or accepted by the patients (
The reduction in ACT provision for patients who were not parasitemic led to a significant increase in the composite indicator of patients appropriately treated of 18 percentage points including all facilities and of 29 percentage points considering only those facilities with ALu in stock. However, while over-prescription of ACT was substantially reduced, under-prescription remained a major problem. Only 56.5% of patients with a positive facility test obtained an ACT in 2012, with particularly poor results in Mwanza, where only 18.2% of positive patients obtained ACT. There was weak evidence of a decrease in the proportion of patients positive by reference blood smear who obtained ACT between 2010 and 2012 overall, and a significant fall in Mwanza, although the percentages of patients testing positive overall were low (9.2% in 2010 and 16.5% in 2012) resulting in small subsamples and large confidence intervals. Poor ACT availability was a major factor in the under-treatment of patients testing positive. ACT stock-outs were present in all regions but especially severe in Mwanza, with around 40% of facilities experiencing complete ACT stock-outs at the time of both surveys. Even at facilities where ALu was in stock, nearly 20% of patients overall with a positive facility test result did not obtain ACTs. Fear of future stock-outs prompting drug rationing or the absence of the appropriate weight-specific blister packs may have discouraged health workers from dispensing ACT to some patients testing positive by the facility test (
While the proportion of patients who obtained an ACT significantly decreased from 2010 to 2012, the proportion of patients receiving antibiotics significantly increased to just under half of all patients. An increase in antibiotic prescription after mRDT introduction was also reported by two other studies in mainland Tanzania (
This study has several limitations. The sampling probability of health facilities was based on the most recent malaria outpatient data available, which may have suffered from some inaccuracies. Health workers may have been more likely to perform diagnostic tests and less likely to dispense antimalarials to negative patients as a result of the team's presence. To reduce this possible source of bias, the study team emphasised to health workers the importance of following their normal procedures. Community members may also have been drawn to the facility because of the presence of the study team in hopes of obtaining drugs for both sick household members and as a reserve for future periods of drug stock-outs. Research assistants screened all patients arriving at the facility carefully, but it is possible that some patients may not have had a true illness.
The 2012 survey took place slightly earlier in the year than the 2010 survey. The peaks in malaria incidence in Tanzania usually occur just after the short rainy season in November–December and just after the long rainy season in March–May, which may have meant that in 2010, Mtwara was visited after the peak, and in 2012, Mwanza was visited before it fully developed. However, taking into account variable weather patterns, late rains in 2010, and lack of entomological data, it is not clear that this would have affected parasitaemia prevalence.
Finally, care should be taken in interpreting facility-level data in isolation, as improvements seen at government health facilities may not necessarily translate to an increase in coverage at the community level. IMPACT2 household surveys in the same three regions in 2010 and 2012 similarly showed that among patients visiting public health facilities for fever, there was a significant increase in the proportion receiving a diagnostic test (from 28.7% to 46.6%), and a significant decrease in the proportion obtaining ACTs (from 57.4% to 46.1%) (Thomson
Tanzania has made major strides in scaling up access to diagnostic testing for malaria within public health facilities and reducing overuse of ACTs by patients without parasitaemia. However, this study has also demonstrated the dramatically negative role that ACT and mRDT stock-outs continue to play in malaria case management. Several initiatives are underway in Tanzania to improve public sector commodity supply, including text-based stock-out reporting systems (
Priorities for further research include investigating reasons for under-prescription of ACTs for patients testing positive, and high levels of antibiotic prescription, and the potential effect on antibiotic resistance. As countries increasingly implement policies of universal testing prior to treatment for malaria, it will be important to address these concerns in order to improve case management for febrile illnesses and appropriately target ACTs.
The authors would like to thank Adam Wolkon for training and advice on PDA programming and Eugenie Poirot and Bhargavi Rao for assistance during training, piloting and start of field work. Many thanks to the field teams, regional and district health officers and study participants. This work was funded by the Bill and Melinda Gates Foundation, through the ACT Consortium.