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Nursing and Health Care (ISSN: 2573-3877)

Cost Effectiveness of Giemsa versus Field’s Staining Technique: Implications for Malaria Diagnosis among Children in a Busy Hospital Setting in Uganda

Juliana Namutundu, Nsobya Samuel Lubwama, Yeka Adoke, Chrispus Mayora and Sebastian Olikira Baine

Avaliable from September, 2018



World  Health  Organization  and  Ministry  of  Health  (Uganda)  recommend use of microscopy for parasitological confirmation of malaria. Microscopy  involves either Giemsa or Fields staining techniques. Ministry of Health prefers and  recommends use of Giemsa staining technique but most health facilities still use Fields  staining technique. The objective of this study was to compare the cost-effectiveness of  Giemsa and Fields staining techniques in order to inform malaria diagnosis policy and  practice in Uganda.

Methods:  This was a cross sectional cost effectiveness analysis from the providers  perspective covering the period between April 25, 2014 and June 15, 2014. The study involved 243 children below five years of age presenting at Acute Care Unit laboratory for  malaria test before admission. Giemsa and Fields staining techniques were compared with Polymerase Chain Reaction as the gold standard. Decision tree analytic model in  TreeAge was used for the cost effectiveness analysis.

Results: Fields and Giemsa staining techniques cost US $ 0.030 and US $ 0.769  respectively. Correctly diagnosed cases were 227 and 230 for Fields and Giemsa  staining  techniques  respectively.  The  proportion  of  correctly  diagnosed  cases  was  93.4% for Fields and 94.7% for Giemsa. Incremental cost effectiveness ratio was 0.35  US $ per additional correctly diagnosed case.

Conclusion:  Fields  staining  technique  was  more  cost  effective  than  Giemsa  staining technique; provided a higher number of correctly diagnosed cases at a lower cost than Giemsa staining technique. Fields staining technique is recommended as  staining technique for malaria diagnosis at the Acute Care Unit of Mulago National Referral Hospital. This implies that even with introduction of more superior staining  techniques for laboratory diagnosis of malaria, Field staining technique is still a cost effective technique to be used in resource limited settings with high malaria burden like Uganda and Africa at large. 


The World Health Organization recommends parasitological confirmation of  malaria either by microscopy or RDT before initiating treatment with ACT, and this is  documented in the Uganda National Malaria treatment guidelines [1,2]. The level of  malaria endemicity, the urgency of diagnosis, the experience of the physician and cost of  the technique are some of the factors that influence the choice of the malaria-diagnostic  technique to use [3]. In turn, the technique and quality of diagnosis determine the  treatment options, treatment (health) outcomes, and level of resource use. Ideally, an  acceptable diagnostic technique should be both cost-effective and provide results that  are consistently accurate and timely in order to have a direct impact on treatment [4].

There are three methods of detecting malaria parasites in peripheral blood;  microscopy, antigen detection using Rapid Diagnostic Tests and Polymerase Chain  Reaction. Microscopy is a recommended method for routine malaria diagnosis  because it allows the identification of different malaria-causing parasites ( Plasmodium  falciparum ,  Plasmodium vivax ,  Plasmodium malariae and  Plasmodium ovale ) and  quantification of parasite density to monitor response to treatment [5]. The Ministry  of Health in Uganda recommends the use of RDT at Health  Centre II & community levels, while microscopy is used at Health  Centre level III and IV, and hospitals [6]. Microscopy itself is  not a magic bullet; cases of misdiagnosis leading to inappropriate  treatment still exist in Uganda. As a result, the practice of treating  all febrile infections with anti-malaria drugs remains an outstanding  challenge [7]. This creates need for appropriate malaria diagnostic  strategies that will promote efficient use of resources, reduce  costs on the management of malaria and address challenges of  presumptive treatment of malaria [8,9]. Microscopy is the major  malaria diagnostic technique used in hospital settings in Uganda.  Microscopy uses either Fields or Giemsa staining techniques.  Fields staining technique is most commonly used in health  centres and hospitals although the Uganda Ministry of Health  recommends use of Giemsa stain [6].

Mulago National referral hospital like other health facilities  mainly uses Fields staining technique for laboratory diagnosis  of malaria. Acute Care Unit, a major pediatric ward at Mulago  National referral hospital has a malaria prevalence ranging from  30-35%, malaria being the leading cause of complications and  death among children less than five years admitted at this ward.  Due to the high malaria prevalence, over 75% of children admitted  to acute care unit are tested for malaria using Fields staining  technique prior to admission therefore the type of management  and treatment offered to these children is influenced by the first  malaria test results. However, both the accuracy of results and cost  of microscopy are determined by the type of stain used. Fields  stain takes a short time to results. Giemsa stain has better staining  properties and recommended for Quality assurance purposes.  Given the limited resources and the need to ensure proper  treatment of children admitted to Mulago National Referral  Hospital, it is important to determine the cost effectiveness of  the staining techniques so as to decide which one is appropriate  to take on. This study set out to determine and compare the  cost effectiveness of Giemsa and Fields staining techniques in  parasitological confirmation of malaria among children under five  years received at the Acute Care Unit of Mulago National Referral  Hospital in order to inform policy and implementation.  


Study design and setting

This was a cross sectional cost effectiveness analysis study  carried out at the Acute Care Unit of Mulago National Referral  Hospital. Acute Care Unit is a 24 hour emergency ward and  reception center for all pediatric nonsurgical patients. It receives  children aged up to 12 years but majority (about 75%) are below  five years. . Upon stabilizing their medical condition, they are  transferred to general pediatric wards for continuation of care.  Acute Care Unit admits 40-50 children daily, has a laboratory  which operates 24 hours daily. Malaria is the leading cause of  morbidity and mortality among children admitted at Acute Care  Unit, Mulago National Referral Hospital and over 90% of these  children undergo a parasitological confirmation test for malaria  before and/or during care. Routine malaria diagnosis at the Acute  Care Unit is by microscopy using Fields staining technique. On  average, 20–30 children less than five years are tested for malaria  daily. There are seasonal variations in the prevalence of malaria in  the ward. The prevalence of malaria among these children ranges  between 20% and 35%.

Study population

The study population was made up of 243 children below five  years of age presenting at Acute Care Unit laboratory for malaria  test before admission.

Sample size determination and sampling  

The study sample size was obtained using Buderers method  [10] for calculation of power in diagnostic tests based on a standard  2 by 2 table for comparing diagnostic tests. This method was used  because determination of effectiveness was based on sensitivity  and specificity of Fields and Giemsa staining techniques. Two  sample sizes were obtained based on the need for adequate sensitivity  and for adequate specificity [10]. Using this method, the number  of patients needed for adequate sensitivity was 243 while that for  adequate specificity was 351. Given the time and resources available  the study used 243 children to determine effectiveness of the staining  techniques. Study participants were selected using consecutive  sampling, a good sampling method when determining effectiveness  or accuracy of diagnostic tests [11]. The study only included  children with caregivers consent. Enrollment and determination  of effectiveness was done from April 25 to June 15, 2014.

Sampling procedure

Study participants were selected using consecutive sampling.  This method has been recommended for use in determining  effectiveness or accuracy of diagnostic tests (Knottnerus and  Muris, 2003). Eligible children were enrolled into the study as they  presented at the acute care unit laboratory for the initial malaria  test prior to admission.

Inclusion criteria

All children below five years who were received at acute care  unit Mulago National Referral Hospital and presented for the  initial malaria test prior to admission were included in the study.

Exclusion criteria

Children below five years who reported to acute care unit  Mulago National Referral Hospital for the initial malaria test  without caregivers consent were not included in the study.

Cost data collection  

The costs of the staining techniques included; direct medical  and direct non-medical costs incurred during malaria diagnosis  using either Fields or Giemsa staining techniques. Direct medical  costs were precisely related to the staining method. They included;  laboratory technologists time, cost of reagents, equipment and  supplies. Direct non-medical costs incurred in the process of testing  were not directly related to the staining method. They included:  costs for utilities like water, electricity and laboratory space. The ingredient approach was used for costing each staining  technique. This approach involved identification, quantification  and valuation of all inputs for the staining techniques in order  to obtain unit costs. This was done for the different steps in the  staining process which included; smear preparation, smear  drying and examination. Costs were obtained in aggregate form and broken down to obtain unit costs in terms of cost per blood  smear. These unit costs were summed up to obtain a unit cost  for each staining technique. This study included costs incurred  while staining of blood smears in either staining techniques  only. Costs for steps that were similar in both techniques were  excluded from the analysis because they equally incurred in both  staining techniques and cannot cause differences in the outcome.  These included costs for; blood sample collection, blood smear  preparation, smear drying and examination. Overhead costs  were assumed to be equally incurred in both staining techniques  and were therefore excluded from the analysis. These included  cost of; reagent storage, building maintenance, cost of hospital/ laboratory administration, cost of reagent preparation and storage,  transportation, cleaning and taxes. Costs of the Polymerase Chain  Reaction test were not included in the analysis since this test was  only used as a gold standard.

The costs incurred during staining in either technique included;  capital costs, reagent costs, labor costs and utility costs. Capital  costs included cost of laboratory space and equipment. Reagent  costs included costs of all reagents that were used during staining.  Labor costs included; Labor laboratory technicians time and cost  of utilities (water and electricity) used during staining.  

Data on costs was obtained in aggregate form and then  disaggregated to come up with unit costs. Cost data was obtained  from the market wholesale price, the administration of Mulago  National Referral Hospital, and National Medical Stores and  General Medical Stores. The United States dollar was used in  this study because it is a widely used currency in most Cost  Effectiveness Analyses and for aiding comparison. The costs were  collected in Uganda shillings and converted to the United States  dollars at the existing exchange rate during study period of 1United  States dollar to 2550 Uganda shillings (

Measurement of effectiveness

Blood samples for determination of effectiveness of Fields  and Giemsa staining techniques were collected from 243 children  below five years of age who presented at Acute Care Unit laboratory  for malaria diagnosis during the study period. Effectiveness of the  staining techniques was determined by the number and proportion  of correctly diagnosed cases as applied in other studies [12-15].  As applied in a similar study [12], Polymerase Chain Reaction  method was used as the gold standard for this study using nested  Polymerase Chain Reaction technique for  Plasmodium falciparum  because Plasmodium falciparum accounts for over 95% of malaria  infections in Uganda. Probabilities for stain effectiveness were  the calculated positive and negative predictive values of the two  staining techniques as compared to Polymerase Chain Reaction  method.  

Cost effectiveness Analysis model

The decision tree analytic model using Tree Age software was  used for the cost effectiveness analysis. Effectiveness probabilities  and values together with the providers costs incurred by either  technique were used to populate the model in order to determine  cost effectiveness of the two staining techniques. The payoffs  for the correctly diagnosed cases were the number of correctly  diagnosed cases, true positive and true negative cases for both  staining techniques while cases that were not correctly diagnosed  (false positive and false negatives cases) had a payoff of zero. In  both staining techniques, the cost payoffs were the unit costs for  the staining technique.

Sensitivity analysis

Use of different sources of costs created uncertainty. In order  to address this uncertainty, sensitivity analysis was carried out on  unit costs of each staining technique. The costs were halved and  doubled in order to get the lower and upper limits of sensitivity  ranges respectively. One-way sensitivity analysis was used since  only one variable was varied.

Ethical Approval

Ethical approval was obtained from the Makerere University  School of Public Health Institutional Review Board. Permission to  conduct the study in Mulago National Referral Hospital was also  obtained from the Mulago National Referral Hospital Research  and Ethics Committee (Protocol MREC539).  

Quality Assurance and Control

All study activities were coordinated and supervised by the  principle investigator (PI) who is a laboratory technologist with  experience in research. The research team comprised of one nurse  and three laboratory technologists, all with more than ten years of  experience in their fields. These were briefed about their activities  prior to data collection by the PI. The PI actively participated in  ensuring quality data collection and documentation. Results  for Giemsa and Fields stains were filed and kept separately.  PCR tests were conducted in a separate and highly specialized  research laboratory by highly qualified laboratory technologists.  Information on blood samples was checked for consistency  with that on the study forms. We ensured uniformity in labeling  on the forms and blood samples. Rounding off of costs during  disaggregation was avoided.


Demographic characteristics of study participants

Table: Demographic characteristics of study participants

Demographic characteristics of study participants


Various costs incurred when using either Fields or Giemsa  staining technique were identified and sorted into three broad  categories; reagent costs, labor costs and equipment costs as  indicated in Table 1. Unit costs were US $ 0.030 and US $ 0.769  for Fields and Giemsa staining techniques respectively. The  percentage of reagent costs as a proportion of total unit costs of  the staining techniques were 5.19% and 0.446% for Fields and  Giemsa staining techniques respectively. Labor costs comprised  of 89.63% and 99.469% of the unit costs of Fields and Giemsa  staining techniques respectively. The corresponding percentage of  equipment costs as a proportion of total unit costs for the staining  techniques were 5.18% and 0.085% respectively. 

Unit costs for the staining techniques 

Table 1: Unit costs for the staining techniques.


Effectiveness of each staining technique was determined by  the number and proportion of cases correctly diagnosed using  Giemsa and Fields staining techniques with PCR method as the  gold standard (Table 2).  Effectiveness probabilities for populating the decision tree  analytic model were calculated and are presented in Table 3. The  numbers of correctly diagnosed cases were 227 and 230 for Fields  and Giemsa staining techniques respectively. The corresponding  proportion of correctly diagnosed cases was 93.4% and 94.7%  respectively. Effectiveness probabilities were calculated using  epidemiological principles for determination of diagnostic accuracy  based on 2X2 table [16]. The probabilities included; the positive and  negative predictive values, and their complementary probabilities.  The calculated probabilities together with the number of correctly  diagnosed cases were populated in the analysis model to obtain  expected values for either staining techniques. The expected values  were the basis for comparison of effectiveness and cost effectiveness.

Stain effectiveness as compared with PCR method

Table 2: Stain effectiveness as compared with PCR method.

Effectiveness Probabilities for the staining techniques

Table 3: Effectiveness Probabilities for the staining techniques.

Cost effectiveness analysis

Cost effectiveness analysis using both costs and number of  correctly diagnosed cases The cost effectiveness analysis indicated that Fields staining  technique was more costs effective than Giemsa staining technique  (Figure 1). Figure 2 provides a graphical presentation of the cost  effectiveness analysis. Since Giemsa had higher effectiveness and higher costs than  Fields staining technique, the graph further emphasizes the  importance of the decision tree analysis as a way of determining  the more cost effective staining technique.

Decision Tree for Cost Effectiveness Analysis

Figure 1: Decision Tree for Cost Effectiveness Analysis.

Cost effectiveness analysis graph

Figure 2: Cost effectiveness analysis graph.

Incremental cost effectiveness analysis ratio ( ICER )

Table 4 indicates the cost effectiveness rankings obtained from  the cost effectiveness analysis. These include; costs, effectiveness  and provided the incremental cost effectiveness ratio for staining  techniques based on the expected values generated in the decision  tree analysis. The incremental costs and incremental effectiveness  were 0.74 US $ and 2.12 correctly diagnosed cases respectively  while the ICER was 0.35 US $ per additional correctly diagnosed  case.

Cost effectiveness rankings

Table 4: Cost effectiveness rankings.

Sensitivity analysis

We conducted one-way sensitivity analysis using TreeAge.  This was done by varying the costs (Table 5) of Fields and Giemsa  staining techniques on assumption that other parameters remained  constant. In both instances, Giemsa staining technique remained  more cost effective than Fields staining technique and the ICER  remained was not affected. The ICER remained constant at 0.35  even with varying these costs.

Sensitivity Analysis Ranges 

Table 5: Sensitivity Analysis Ranges.


The World Health Organization and Uganda Ministry of  Health recommends microscopy using Giemsa staining technique  for the parasitological confirmation in the diagnosis of malaria [6].  Microscopy using Giemsa staining technique provides quality test  results and is considered to be more effective than Fields staining  technique. However, its cost effectiveness is still debated. Most  health facilities in Uganda that still use Fields staining technique  argue that Giemsa has a high time to results compared to Fields  stain which increases its cost.  

Costs of staining techniques

Unit costs for Fields and Giemsa staining techniques were  0.030US $ and 0.769 US $ respectively. This implied the cost of  Giemsa staining technique was 25.6 times higher than that for  Fields staining technique. Staining with Giemsa takes 32 minutes  compared to Fields that takes 1 minute and 8 seconds. Labor  costs were the highest cost drivers in both staining techniques  constituting of 89.63% and 99.469% of unit costs for Fields and  Giemsa staining techniques respectively. This finding is similar to  what was found in previous studies on costs of malaria diagnosis  using microscopy which also reported labor costs as the highest  cost driver [12, 14, 15].  

There was a slight difference (0.001863 US $ ) in reagent costs  incurred in the staining techniques although the proportion of  reagent costs was higher for Fields staining technique compared  to that for Giemsa staining technique. Reagent and equipment  costs for the Fields staining technique were almost equal at 5.19%  and 5.18% of the unit cost respectively. Proportions of reagent  and equipment costs were higher for Fields staining technique  (5.19% and 5.18%) than for Giemsa staining technique (0.085%  and 0.446%). This is because unlike Giemsa, Fields staining  technique requires more reagents and equipment but reagents  needed in Fields staining technique are cheaper than those for  Giemsa staining technique. Fields staining technique was found  to be more cost saving and this partly accounts for its preference in  high malaria diagnosis workload in resource limited settings Effectiveness of the staining techniques Giemsa staining technique was more effective than Fields  staining technique. The number of correctly diagnosed cases  was 227 and 230 for Fields and Giemsa staining techniques  respectively. The corresponding proportion of correctly diagnosed  cases was 93.4% and 94.7% respectively. There was a slight  difference in number and proportion of correctly diagnosed cases  of malaria by the two staining techniques.  

The sensitivity of Fields and Giemsa staining techniques were  54.9% and 99.5% respectively while sensitivity was 60.6% and 100%  for Fields and Giemsa staining techniques respectively. This results  do not very different from those of a similar study that reported  47.2% and 46.1% sensitivity and 93.4% and 97.2% specificity for  Fields and Giemsa respectively [17].

The positive predictive values were 0.947 and 1.00 while  corresponding negative predictive values were 0.933 and 0.942 for  Fields and Giemsa staining techniques respectively. The expected  effectiveness value for Giemsa staining technique was 183.24 while that for Fields staining technique was 181.12. This indicates that  Giemsa was slightly more effective than Fields staining technique.

Cost effectiveness of Giemsa compared to Fields staining  technique

Fields staining technique was more cost effective than Giemsa  staining technique. This is because the cost of Giemsa staining  technique is higher than Fields staining technique; yet, Giemsa  staining technique has a slightly higher effectiveness than fields  staining technique. The incremental cost effectiveness ratio was  0.35 $ per additional correctly diagnosed case of malaria. This  implies that based on the findings of this study, every additional  correctly diagnosed case of malaria obtained by moving from  Fields to Giemsa staining technique cost the provider 0.35 US  $ which is 8.2 times higher than the unit cost of Fields staining  technique.  

Sensitivity analysis

Results of the sensitivity analysis indicated that the Incremental  Cost Effectiveness Ratio was not affected by varying the costs of  the staining technique. Based on the expected values from the cost  effectiveness analysis it remained constant at 0.35. The results of  the sensitivity analysis indicated that the cost effectiveness analysis  model was robust.

Study Limitations

The use of number and proportion of correctly diagnosed cases  of malaria as the outcome posed a limitation for this study. This is  an intermediate outcome that is assumed to be linked to improved  final outcome, recovery from disease. The link between correctly  diagnosing a case, optimal clinical management of the patient, and  a satisfactory health outcome may be difficult to prove without a  close patient follow up. Within the scope of this study, it was not  possible to estimate the link between incorrectly diagnosed cases  of malaria and the final clinical outcome. This is because no patient  follow up was made hence further research will be required in this  area. Another limitation of this study was use of the providers  perspective. However, in this study the provider perspective  was used because we only considered the costs of providing  these staining techniques, although there are some indirect costs  incurred by the consumer which were not included.

Confounding Factors

This study had minimal confounding. The possible source  of confounding for this study could have been the difference in  malaria slide preparation and microscopy slide reading. This was  addressed by using qualified and highly experienced (over 10  years experience) laboratory technologists in laboratory diagnosis  of malaria in a busy hospital setting.  


Drawing from findings of this study, Field’s staining technique was more cost effective than Giemsa staining technique. It provided a higher number of correctly diagnosed cases of malaria at a lower cost than Giemsa staining technique. With Uganda statistics of 2013 indicating a Gross Domestic Product (GDP) per capita of 1365.13 US dollars, an of ICER of 0.35 US dollars indicates that Field’s staining technique is affordable. This study therefore recommends the use of Field’s staining technique for routine microscopy for the parasitological confirmation of malaria diagnosis limited resource settings like the Acute Care Unit at Mulago National Referral Hospital and Uganda at large, and in other low income countries. Implementation of the Ministry of Health’s recommendation to use Giemsa staining technique should be promoted when adequate resources have been made available to support it. This study highlights the need to incorporate cost effectiveness analyses in decision making process to inform policy and implementation.

Competing Interests

 The authors declare that they have no competing interests 

Authors’ Contributions

NJ participated in the inception, design, implementation of the research, analysis and interpretation of findings as well as writing the manuscript. NSL participated in the inception and design of the research and also conducted PCR assays. YA was involved in drafting the manuscript through providing critical review and gave final approval of the version to be published. CM participated in the analysis, interpretation of data and was involved in drafting the manuscript. SOB participated in analysis, interpretation of data, drafting the manuscript and gave final approval of the version to be published. 

Authors’ Information

NJ, currently Research Associate at Makerere University School of Public Health was a student of Master of Health Services Research at Makerere University at the time of conducting the research. NSL is the Laboratory Director of the Makerere University-University of San Francisco California Molecular Laboratory under the Infectious Diseases Research Collaboration. YA is a senior Epidemiologist at the Uganda Malaria Surveillance Project. CM is an assistant Lecturer under the Department of Health Policy, Planning and Management at the School of Public Health, Makerere University. SOB is a Senior Lecturer under the Department of Health Policy, Planning and Management at the School of Public Health, Makerere University


This research was made possible by Uganda Malaria Clinical Operational and Health Services (COHRE) Training Program at Makerere University, Grant #D43-TW00807701A1, from the Fogarty International Center (FIC) at the National Institutes of Health (NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of FIC or NIH.


1. Ministry of Health M.O.H, (2008) Guidelines for treatment of malaria.

2. WHO (2012) World Malaria report.

3. Tangpukdee N, Duangdee C, Wilairatana P, Krudsood S. Malaria diagnosis: a brief review. (2009) Korean J Parasitol 47: 93-102.

4. WHO (2013) WHO Bulletin.

5. Bronzan RN, McMorrow ML, Kachur SP. Diagnosis of malaria: challenges for clinicians in endemic and non-endemic regions. (2008) Mol Diagn Ther 12: 299-306.

6. Ministry of Health M.O.H (2013) Uganda National Guidelines for implementation of Parasite Based Diagnosis of Malaria, Uganda.

7. Ndyomugyenyi R, Magnussen P, Clarke S. Diagnosis and treatment of malaria in peripheral health facilities in Uganda: findings from an area of low transmission in south-western Uganda. (2007) Malar J 6: 39.

8. Nankabirwa J, Zurovac D, Njogu JN, Rwakimari JB, Counihan H, et al., Malaria misdiagnosis in Uganda--implications for policy change. (2009) Malar J 8: 66.

9. Namagembe A, Ssekabira U, Weavr MR, Blum N, Burnett S, et al., Improved clinical and laboratory skills after team-based, malaria case management training of health care professionals in Uganda. (2012) Malar J 11: 44.

10. Buderer NM. Statistical methodology: I. Incorporating the prevalence of disease into the sample size calculation for sensitivity and specificity. (1996) Acad Emerg Med 3: 895-900.

11. Knottnerus J, Muris J. Assessment of the accuracy of diagnostic tests: the cross-sectional study. (2003) Journal of clinical epidemiology 56:1118-1128.

12. Batwala V, Magnussen P, et al., Cost-effectiveness of malaria microscopy and rapid diagnostic tests versus presumptive diagnosis: implications for malaria control in Uganda. (2011) Malar J. 10: 372.

13. Shillcutt S, Morel C, et al., Cost-effectiveness of malaria diagnostic methods in sub-Saharan Africa in an era of combination therapy. (2008) Bulletin of the World Health Organization, 86: 101-110.

14. Uzochukwu BS, Obikeze EN, Onwujekwe OE, Onoka CA, Griffiths UK. Cost-effectiveness analysis of rapid diagnostic test, microscopy and syndromic approach in the diagnosis of malaria in Nigeria: implications for scaling-up deployment of ACT. (2009) Malar J 8: 265.

15. Chanda P, Castillo-Riquelme M, Masiye F. Cost-effectiveness analysis of the available strategies for diagnosing malaria in outpatient clinics in Zambia. (2009) Cost Effectiveness and Resource Allocation. 7: 5.

16. Szklo M, Nieto FJ, Miller D. Epidemiology: beyond the basics. (2001) American Journal of Epidemiology. 153: 821-822.

17. Batwala V, Magnussen P, Nuwaha F. Are rapid diagnostic tests more accurate in diagnosis of Plasmodium falciparum malaria compared to microscopy at rural health centres. (2010) Malar J 9: 349.

*Corresponding author

Juliana Namutundu, Makerere University, School of Public Health, P.O.BOX 7072, Kampala, Uganda, Tel: +256 41 4533332 E-mail:


Namutundu J, Lubwama NS, Adoke Y, Mayora C, Baine SO (2016) Cost Effectiveness of Giemsa versus Field’s Staining Technique: Implications for Malaria Diagnosis among Children in a Busy Hospital Setting in Uganda. NHC 106: 26-32