Supplement article - Research | Volume 5 (1): 1. 16 Feb 2022 | 10.11604/JIEPH.supp.2022.5.1.1227

Impact of turnaround time in delivery of Covid-19 results and surveillance: a case of points of entry, Uganda

Joyce Owens Kobusingye, Mitima Jean-Marie Limenyande, Harriet Mayinja

Corresponding author: Mitima Jean-Marie Limenyande, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda

Received: 08 Jul 2021 - Accepted: 14 Dec 2021 - Published: 16 Feb 2022

Domain: Public health

Keywords: COVID-19, turnaround time, results, points of entry, Uganda

This articles is published as part of the supplement Preparedness and response to COVID-19 in Africa (Volume 2), commissioned by AFRICAN FIELD EPIDEMIOLOGY NETWORK (AFENET).

©Joyce Owens Kobusingye et al. Journal of Interventional Epidemiology and Public Health (ISSN: 2664-2824). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article: Joyce Owens Kobusingye et al. Impact of turnaround time in delivery of Covid-19 results and surveillance: a case of points of entry, Uganda. Journal of Interventional Epidemiology and Public Health. 2022;5(1):1. [doi: 10.11604/JIEPH.supp.2022.5.1.1227]

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Impact of turnaround time in delivery of Covid-19 results and surveillance: a case of points of entry, Uganda

Impact of turnaround time in delivery of Covid-19 results and surveillance: a case of points of entry, Uganda

Joyce Owens Kobusingye1, Mitima Jean-Marie Limenyande1,&, Harriet Mayinja2


1School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda, 2Department of Integrated Epidemiology Surveillance and Public Health Emergencies, Points of Entry, Ministry of Health - Uganda



&Corresponding author
Mitima Jean-Marie Limenyande, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda.




Introduction: Uganda implemented strict border control measures at an early stage of the COVID-19 pandemic in 2020 at more than a hundred points of entry (POE) connecting her to neighboring East African countries; Tanzania, Kenya, Rwanda and Democratic Republic of Congo. This came with minimum restrictions to truck drivers to keep economies vibrant with continued trade though it increased the risks of COVID-19 spread. Study Objectives:To assess factors affecting the turnaround time in sample collection, estimate the turnaround time of delivery of COVID-19 test results and its impact on COVID-19 surveillance at different POE in Uganda.


Methods: We conducted a cross-sectional study using a mixed methods approach, from August 2020 to December 2020. Thirty-three (33) POE were purposively selected to participate in the study. Key informant interviews were also conducted with some POE staff at the Public Health Emergency Operation Center (EOC).


Results: We interviewed 33 POE focal persons and 5 key informants, with a mean age of 35 years (sd: 6.8), among them 7 (18.42%) were female. Eight (24.24%) POE were selected from the Northern region, 6 (18.18%) Central region, 11 (33.33%) Western region and 8 (24.24%) Eastern Uganda. The average turnaround time was 3 days and the minimum waiting time was 1 day whereas the maximum was 7 days. Factors affecting turnaround time were the number of samples taken from travelers, distance to the laboratory, lack of transportation means, lack of electronic gadgets to access online results or lack of power to charge the gadgets used. The impact of long turnaround time was poor management of travelers and the delays in reporting which generally affected outbreak surveillance.


Conclusion: Delay in receiving results could not allow the staff in the field to make timely decisions that could allow them to manage people waiting to cross the border during the pandemic which resulted in several operational challenges at the POE. High volume POE should therefore have their own laboratory on site to manage the increasing number of travelers and reduce the turnaround time



Introduction    Down

Turnaround time (TAT) is a major factor that allows the assessment of performance for all the services offered in a laboratory [1,2]. A shorter TAT increases satisfaction to both the patient, the clinician and the laboratory personnel at a point. On the clinician´s side, satisfaction is geared more at having a basis on which he can give treatment and make informed decisions [3,4] regarding a patient´s health or a health event. To the laboratory personnel, focus is more on meeting the expectations of clients - the patient´s and the clinician [3]. The definition of TAT has itself been a source of disagreement among laboratory workers and clinicians: At what point do we account for turnaround time and to what end? Despite the different views, the consensus is that laboratory TAT covers three major phases; the pre-analytic phase; that starts when the examination is ordered to preparing the sample in the laboratory, the analytic phase; when tests are performed in the laboratory and the post-analytic phase; when results are reported back so action or a decision is made [1-3].


Shortening the laboratory TAT has for long been a goal in health care provision [5] and many have invested a lot of resources to achieve this. It ought to be understood that, people in health emergency and health practitioners in outbreak responses need results fast during any intervention. This concern arises out of the need to save lives and thereafter offer treatment [6,7]. The improvements made around TAT have been aimed at shortening the time along the different paths - from picking the samples to availing of results. Distance from the sample collection point to the laboratory is another vital factor [4,8,9]. But the use of mobile laboratory in field responses ensures that results are provided in the shortest time possible [3,10]. Field teams can now use mobile polymerase chain reaction (PCR) equipment, to allow for access of results as fast as - less than half an hour [8,11]. The number of samples received from different sample collection points in an area and the priority given to them at the laboratory also plays a key role in determining the TAT. Timely communication between healthcare workers and the laboratory professionals is vital in ensuring mutual understanding and collaboration after the samples have been collected and delivered at the laboratory. This may include informing the healthcare workers about potential reasons for delayed results; system breakdown, workload and certain test menu limitations so they inform the travelers waiting for results in time [12]. The ideal situation to reduce TAT would be to bring the laboratory services closer to the sample collection points. With the COVID-19 pandemic, the increase in demand of laboratory services has created longer TAT and shortage of supplies used in sample collection [13].


In the context of COVID-19 pandemic, the turnaround time for results can increase the risk of transmission of the virus from those waiting for results –who may be asymptomatic– to more susceptible people [14, 15]. In Uganda for example, as the truck drivers waited in long queues for their results at the different POE, the longer they continued to interact with the communities the higher was the risk of exposing them to the virus and thus the increase in the number of cases at border points [16]. At the start of COVID-19 pandemic in Uganda in 2020, the Ministry of Health (MOH) implemented strict border control measures at an early stage of the pandemic to reduce transmission. All POE connecting Uganda to neighboring countries were closed, with minimum restrictions to truck drivers to keep economic environment vibrant [17].


To facilitate smooth operation, the Eastern Africa Community (EAC) Secretariat and its Partner States rolled out the Regional Electronic Cargo and Drivers Tracking System (RECDTS) to enable the issuance of the EAC COVID-19 digital certificates recognized by Partner States to ease movement across the border. Despite its reliability, there are notable challenges regarding its effectiveness in providing timely certificates to truck drivers; requiring one to have a smartphone or its equivalent and being connected to internet to access the negative results [18]. The TAT in sample collection, transportation to laboratory and the ability to access results plays an important role in facilitating surveillance especially now in the fight against the COVID-19 pandemic. This study therefore aimed at assessing the factors determining turnaround time in sample collection, estimate the turnaround time of delivery of COVID-19 test results at different POE and its impact on surveillance in Uganda.



Methods Up    Down

Study setting


The short study was carried out at the Emergency Operation Center (EOC) field site in Kampala district with a few field visits at the different POE from August 2020 to December 2020. The EOC is a co-ordination center for all emergency related responses: COVID-19, Measles, Tuberculosis, Anthrax, Cholera and EVD, with COVID-19 response at the helm of it at the moment - 2020. POE surveillance is a sub-pillar under the surveillance pillar and reports on 58 operational POE around Uganda during the COVID-19 pandemic, including Entebbe international airport.


Study participants


The study participants were thirty-three (33) POE contact persons who were purposively selected because they worked at these respective points and had key information regarding POE operations on the ground during the COVID-19 pandemic. We also engaged five (5) key informants who were POE officers at the EOC in charge of different regions where the POE are located and are charged with reporting during the surveillance committee meetings Table 1.


Study design


We conducted a cross-sectional study where we used both quantitative and qualitative methods. Participants were subjected to a set of both structured and semi-structured questionnaires during the interviews. We also carried out a secondary data analysis of the POE situation reports submitted at the EOC during surveillance committee meeting every Monday, Wednesday and Friday.


Sampling procedure


We ranked the POE according to the number of travelers screened at their border points in four months (May to August 2020). The first twenty POE had registered over 75 percent of the total travelers that crossed border points during the period were all included in our sample. Also, all the positive cases recorded from border points since the start of the epidemic in the country; were identified from those POE. Among the 20 POE, 7 were from the Western region, 5 from the northern, 3 from the central 5 in the Eastern. We conveniently selected 13 more POE–following the ranking we used –to ensure we have a perspective from the POE with fewer travellers.


Study variables


The dependent variable in the study was turnaround time of sample collection and delivery of COVID-19 test results. The independent variables were; location of POE, number of samples collected, transportation used to take the sample to the laboratory, infrastructure for isolation and quarantine of people waiting for results, number of sample collection points, functionality of sample tracking systems, interval of sample collection, number of testing centers, volume of people at site, availability of sample collectors, and availability of funds to pay for the test by travelers.


Data collection methods


Interviews were conducted via phone calls for staff at POE sites and face to face for key informants at the EOC. We used a set of structured and semi-structured questionnaires with 13 questions to answer our study objectives. All respondents were called within two weeks, from 12th October 2020 to 25th October 2020, and each phone call lasted approximately 15 to 20 minutes on average. Information was also obtained from key informants to check for consistency of responses obtain from the staff at POE sites.


Data management and analysis


Information from each POE was kept separately in a book. After verification of the information from key informants, the data from open questions was coded and analyzed manually. The codes were grouped into categories and the emerging themes were then identified from the records and given an overall meaning.


A different approach was used for the close-ended questions. For questions answered by yes or no we summarized using count and percentage. For age and the turnaround time for covid-19 results, we summarized using mean, median and standard deviation. The whole analysis was done using Microsoft Excel 2016– it was also used to generate the summary table.


Ethical consideration


This study was approved by Makerere University School of Public Health. Consent was sought from respondents and the POE overall focal person at the EOC, and later the respondents were also informed prior of the impeding interview before the interviews were made.



Results Up    Down

Availability of testing laboratory and laboratory personnel


Our assessment found that out of the 33 POE contacted, majority (30 POE) had a laboratory personnel onsite to collect samples from travelers Table 2. Usually, the laboratory technician transported the samples collected to the laboratory located either within the district or outside of it.


Regarding the number of laboratories in the district, we noted that MOH increased the number of laboratories in the districts and regions - including mobile laboratory to meet the demand for testing in different regions. Those that didn´t have testing laboratory or if the nearest laboratory had many samples waiting to be tested or had a technical issue; samples were taken to other laboratories in the region or in Kampala. The complexity of this path was increasing the turnaround time for results but also created more risk in damaging the samples due to longer travels.


We noted also that provision of services offered by the laboratory personnel was affected by several events apart from breakdown of some of the mobile laboratories installed. When the number of travelers increased— due to easing of the travel ban and movement in the country, the situation at the POE worsened as the number of samples to be tested increased. Some of the POE did not have permanent shelters and were subject to natural conditions like heavy rain or were destroyed due to aging and needed to be replaced several times throughout the epidemic. That led to failure to meet the sample collection requirement that affected the COVID-19 response at those specific POE.


COVID-19 supplies


During the interviews, the POE focal personnel revealed that they didn´t experience stock out of COVID-19 supplies. Those that did, got in touch with the responsible personnel at the district or central office at the MOH and were restocked within a shortest period Table 2. However, not all the required supplies were available and in sufficient number whereby some of the PPEs were sometime not available. Despite that fact, laboratory technicians had to adapt to those difficulties to keep the flow of activities.


Transport means used at POE


Twenty-seven POE out of 33 used vehicles to deliver the samples collected from the POE to the laboratory Table 2. Sometimes, the vehicle was given for a short period by a partner supporting the POE during Covid-19 pandemic. The other means of transportation was motorcycle and public means, reported respectively by 4 and 2 POE; but this risked the samples being damaged due to poor storage and nature of bad roads at some POE. In addition, at some sites, the collected samples did not go through a straight path; meaning from the POE where the sample was collected to the laboratory where the test will be performed. This situation was frequent for POE without a laboratory within the same district thus the samples from different locations including POE, were gathered to another sample collection point (like a health facility) and form there, a common means of transport was used to take the samples to the laboratory located miles away. That was done mostly once in a day and in the evening; after all the samples collected during the day have reached the health facility used as collection point.


Public transportation was used in rare and particular situations. The situations occurred when the provided means of transport had broken-down while an important number of travelers were waiting for their COVID-19 results.


Average waiting time for results


After the long path of samples, results could be accessed online by the POE staff. The median waiting time was three days with at least one day and maximum of seven days. Outlier situations were reported by few POE which had to wait up to seven (7) days Table 2. Several reasons contributed to this difference in turnaround time as discussed herein. For those outlier situations, among the explanations were the POE focal people forgetting to print results for the system.


Ability to access results from the Result Dispatch System (RDS) dashboard


Although results were uploaded on the COVID-19 online RDS developed specifically for quick access to results, some support staff could not access the dashboard. Majority reported the lack of internet at the POE site and/or electricity to power the gadgets they were using Table 2. For those who didn´t have electronic gadgets, they had to wait for other persons to either send them the printed hard copies of the results or the soft copies were sent through another assigned person.


Willingness to pay for a COVID-19 test


The payment for the test was implemented to ease on the high expenses that the government was incurring to support the national response. Truck drivers were ready and willing to pay for the COVID-19 tests because they needed the COVID-19 certificate so they can deliver their goods to the final destinations Table 2. Other travelers would either not afford to pay for the test or found it expensive and would request that the price is reduced. Those who were not willing to pay—especially the border communities argued that they have relatives across the border and couldn´t be subjected to daily testing if they had to visit them.


Implementing the RECDTS eased the testing workload at the POE and facilitated access to results for truck drivers. Operations at the different borders using the system were improved. Drivers had the option to pay and do the test before reaching the border, from any testing site in the country where they come from. The limitation to this was the lack of smart mobile phones by some drivers. The personal result had to be uploaded on an electronic gadget like a smart-phone and its validity would then be verify at every check point along the different POE.


Impact of long turnaround time for results on COVID-19 activity at POE


Most of the POE did not have an isolation or quarantine facilities. They did not have a waiting area to accommodate the huge number of travelers waiting for results. Majority of the POE staff required travelers to wait for their results from either the trucks or go back home. Finding contacts of these travelers if results turn out to be positive was through contact tracing. However, the practicability of this approach was not straight forward; some contacts of cases were not willing to cooperate due to fear and stigma around COVID-19. The list of contacts could sometime not be listed exhaustively as many days have passed since the test was requested. When cases soared, logistic issues came on board as people to be evacuated became many while the process required more personnel. Besides management challenges with risk of spreading the diseases while waiting for results; travelers had to wait for days before having their results that contributed to delays in transportation of goods. Clearly, the long turnaround time had negative impact on POE - poor performance regarding the management of suspected cases of COVID-19 due to delay of decision making.



Discussion Up    Down

The turnaround time for results was generally longer at POE, which is the same situation that happened elsewhere as the number of COVID-19 cases increased [7]. Throughout the epidemic countries worked hard to reduce the turnaround time for results; up to less than 24hr for many and this was achieved through better testing approaches and use of mobile laboratories to eliminate transportation of samples to distant places [4,9,19]. With Uganda, the samples collected from the POE were sent to other districts miles away where the laboratories were not in the district. MOH therefore increased the number of laboratories that could perform the tests in the different regions although the facilitating supplies could not meet the demand given the soaring number of cases.


The lack of medical supplies noticed at the POE was a general trend noticed globally and the high demand for medical supplies from medical facilities and public health implementing partners could equally not be met by manufacturing industries [20,21]. Even though there was lack, health workers at the POE had to adjust to the situation; laboratory technicians had to work without or repeatedly used the same protective equipment´s which increased the risk to getting infected with COVID-19.


The role of electronic software has also proved to be of relevance in reducing the turnaround time for results during the COVID-19 pandemic because different people accessed their results occasionally [22] and for Uganda the RDS played this key role. However, there were a few challenges on the user´s side; lack of battery power and gadgets to access the results. The approach used in Taiwan [23] went far by tracking infected persons via their electronic devices and the same approach was is used in the EAC region for truck drivers - RECDTS.


The noted impact of long turnaround time was the delay in decision making at the POE, for stakeholders and reporting which generally hindered surveillance during the outbreak [6,14]. The longer the time to dispatch samples and deliver results, the more challenges in the operations of POE activities especially regarding handling travelers who were probable cases. This resulted into community transmissions because travelers continued to associate with the local population in the area as they waited for their results


Study Limitations


This study analyzed turnaround time using POE focal person judgment. Also, it did not include the laboratory component to assess the analytical process of samples delivered. An analysis tracking samples from the point of collection at the POE, throughout their journey - including the laboratory - until results are released, would also give a good insight on the other factors affecting the turnaround time for COVID-19 results.



Conclusion Up    Down

The COVID-19 pandemic has created a public health crisis that can be mitigated only with implementation of programs designed specifically to address the needs that arise occasionally given the high rate of community transmissions right. We therefore conclude that surveillance should prioritize accessibility of testing facilities, minimize sample-to-answer time; analytical limits test results and train staff on administrative activities that need to be carried out on site to manage any related outbreak.

What is known about this topic

  • Turnaround time (TAT) is a major factor that allows for the assessment of performance for all the services offered in a laboratory
  • Long TAT can delay appropriate care for patients waiting for results
  • In the context of COVID-19 pandemic, the turnaround time for results was generally increased due to high demand of laboratory services and shortage of supplies.

What this study adds

  • The TAT for COVID-19 results was long at different Points of Entry in Uganda
  • The different factors that increased TAT could be modified to improve accessibility to COVID-19 results
  • The staff in the field were obliged to postpone important decision that could improve manage people waiting to cross the border during COVID-19 pandemic which resulted in several operational challenges at the POE



Competing interests Up    Down

The authors declare no competing interests




The findings in this report are those of the authors.



Authors' contributions Up    Down

Joyce Owens Kobusingye and Mitima Jean-Marie Limenyande: Conception and design, acquisition of data, analysis and interpretation of data, drafting the paper, revising the manuscript for important intellectual content and final approval of the version to be published. Harriet Mayinja: Acquisition of data, revising the manuscript critically for important intellectual content and final approval of the version to be published. All authors read and approved the final version of the manuscript.



Tables Up    Down

Table 1: Socio-Demographic Characteristic of respondents and Location of POE

Table 2: Summary analysis of key findings



References Up    Down

  1. Goswami B, Singh B, Chawla R, Gupta VK, Mallika V. Turn Around Time (TAT) as a Benchmark of Laboratory Performance. Indian J Clin Biochem. 2010 Oct; 25(4):376-9. PubMed | Google Scholar

  2. Pati HP, Singh G. Turnaround Time (TAT): Difference in Concept for Laboratory and Clinician. Indian J Hematol Blood Transfus. 2014 Jun; 30(2):81-4. PubMed | Google Scholar

  3. Hawkins RC. Laboratory turnaround time. Clin Biochem Rev. 2007 Nov; 28(4):179-94. PubMed | Google Scholar

  4. Yang Q, Meyerson NR, Clark SK, Paige CL, Fattor WT, Gilchrist AR, Barbachano-Guerrero A, Healy BG, Worden-Sapper ER, Wu SS, Muhlrad D, Decker CJ, Saldi TK, Lasda E, Gonzales PK, Fink MR, Tat KL, Hager CR, Davis JC, Ozeroff CD, Brisson GR, McQueen MB, Leinwand L, Parker R, Sawyer SL. Saliva TwoStep for rapid detection of asymptomatic SARS-CoV-2 carriers. medRxiv [Preprint]. 2021 Feb 16:2020.07.16.20150250. PubMed | Google Scholar

  5. Holland LL, Smith LL, Blick KE. Reducing laboratory turnaround time outliers can reduce emergency department patient length of stay: an 11-hospital study. American journal of clinical pathology. 2005 Nov 1; 124(5):672-4. . Google Scholar

  6. Larremore DB, Wilder B, Lester E, Shehata S, Burke JM, Hay JA, Milind T, Mina MJ, Parker R. Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance. medRxiv [Preprint]. 2020 Sep 8:2020.022.20136309. PubMed | Google Scholar

  7. McGarry BE, SteelFisher GK, Grabowski DC, Barnett ML. COVID-19 Test Result Turnaround Time for Residents and Staff in US Nursing Homes. JAMA Intern Med. 2021 Apr 1; 181(4):556-559. PubMed | Google Scholar

  8. Lee-Lewandrowski E, Corboy D, Lewandrowski K, Sinclair J, McDermot S, Benzer TI. Implementation of a point-of-care satellite laboratory in the emergency department of an academic medical center: impact on test turnaround time and patient emergency department length of stay. Archives of pathology & laboratory medicine. 2003;127(4):456-60. .

  9. Muraoka M, Tanoi Y, Tada T, Mizukoshi M, Kawaguchi O. Quickly and simply detection for coronavirus including SARS-CoV-2 on the mobile real-time PCR device and without RNA Extraction. medRxiv. 2020 Jan 1. . Google Scholar

  10. Guss DA, Chan TC, Killeen JP. The impact of a pneumatic tube and computerized physician order management on laboratory turnaround time. Annals of emergency medicine. 2008 Feb 1;51(2):181-5. . Google Scholar

  11. Patel S, Smith JB, Kurbatova E, Guarner J. Factors that impact turnaround time of surgical pathology specimens in an academic institution. Human pathology. 2012 Sep 1;43(9):1501-5. . Google Scholar

  12. Tan SS, Yan B, Saw S, Lee CK, Chong AT, Jureen R, Sethi S. Practical laboratory considerations amidst the COVID-19 outbreak: early experience from Singapore. Journal of Clinical Pathology. 2021; 74:257-260. Google Scholar

  13. Paczos TA. Mounting a regional response to the COVID-19 pandemic: another reason to “keep” your lab. Archives of Pathology & Laboratory Medicine. 2020 Nov 1; 144(11):1321-4. . Google Scholar

  14. Rong X, Yang L, Chu H, Fan M. Effect of delay in diagnosis on transmission of COVID-19. Mathematical Biosciences and Engineering. 2020; 17(3):2725-40. Google Scholar

  15. Omori R, Mizumoto K, Chowell G. Changes in testing rates could mask the novel coronavirus disease (COVID-19) growth rate. International Journal of Infectious Diseases. 2020 May 1; 94:116-8. . PubMed | Google Scholar

  16. Bajunirwe F, Izudi J, Asiimwe S. Long-distance truck drivers and the increasing risk of COVID-19 spread in Uganda. Int J Infect Dis. 2020 Sep; 98:191-193. PubMed | Google Scholar

  17. Nakkazi E. Obstacles to COVID-19 control in east Africa. Lancet Infect Dis. 2020 Jun; 20(6):660. PubMed | Google Scholar

  18. Bell D, Hansen KS, Kiragga AN, Kambugu A, Kissa J, Mbonye AK. Predicting the Impact of COVID-19 and the Potential Impact of the Public Health Response on Disease Burden in Uganda. Am J Trop Med Hyg. 2020 Sep; 103(3):1191-1197. PubMed | Google Scholar

  19. Kim YJ, Sung H, Ki CS, Hur M. COVID-19 Testing in South Korea: Current Status and the Need for Faster Diagnostics. Ann Lab Med. 2020 Sep; 40(5):349-350. PubMed | Google Scholar

  20. Gereffi G. What does the COVID-19 pandemic teach us about global value chains? The case of medical supplies. J Int Bus Policy. 2020 Jul 15:1-15. PubMed | Google Scholar

  21. Ranney ML, Griffeth V, Jha AK. Critical supply shortages–the need for ventilators and personal protective equipment during the Covid-19 pandemic. New England Journal of Medicine. 2020 Apr 30; 382(18):e41. Google Scholar

  22. Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. The Lancet infectious diseases. 2020 May 1;20(5):533-4. . Google Scholar

  23. Wang CJ, Ng CY, Brook RH. Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing. JAMA. 2020; 323(14):1341-1342. Google Scholar































Impact of turnaround time in delivery of Covid-19 results and surveillance: a case of points of entry, Uganda


Impact of turnaround time in delivery of Covid-19 results and surveillance: a case of points of entry, Uganda


Impact of turnaround time in delivery of Covid-19 results and surveillance: a case of points of entry, Uganda

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