Journal of HIV & Retro Virus Open Access

Keywords

Acute HIV infection; Enzyme immunoassay; HIV testing and counseling; Acquired immunodeficiency syndrome; Sub-Saharan Africa

Acronyms

AHI: Acute HIV Infection; AIDS: Acquired Immunodeficiency Syndrome; EIA: Enzyme Immunoassay; HIV: Human Immunodeficiency Virus; HTC: HIV Testing and Counseling; NAT: Nucleic Acid Testing; POC: Point-of-Care; STI: Sexually Transmitted Infection; SSA: Sub-Saharan Africa

Introduction

Human immunodeficiency virus (HIV) infection progresses through different stages namely: early including acute, chronic, and late stage [1]. Acute HIV Infection (AHI) spans from the acquisition of the virus to the presence of HIV-specific antibodies after a rapid rise and peak of plasmatic viral load, whereas early HIV infection which include acute stage is the period running from HIV acquisition to the viral set point [1].

AHI has impact on both patient management and public health interventions targeting HIV/AIDS epidemic [2]. Much attention has been recently directed towards AHI because of its possible contribution to the growth of the epidemic [3]. The ongoing unchanged HIV incidence in the era of treatment as a prevention intervention may be attributable in part, to current programs failing to diagnose and treat AHI [4]. With regard to the patient management; diagnosing and treating AHI results on the control of viral load at the earlier stage, lower viral set point, reduction of the number of infected cells, limitation of the latent pool of HIV-1 infected CD4+ T cells, and the preservation of the immune function [5]. Researches on AHI in low and middleincome countries are emerging [6]. However, the state of current evidence on AHI has not been yet systematically investigated in Sub-Saharan Africa (SSA).

The objectives of this review is to answer the following questions regarding AHI in SSA: (a) what is the contribution of the acute stage to the spread of HIV infection; (b) what are the clinical manifestations and risk-score algorithm for AHI in place, and (c) what strategies are required for the diagnosis and treatment of AHI at large scale? For the purpose of this review the term acute HIV, early HIV, primary HIV infections are used interchangeably.

Contribution of the acute stage to HIV transmission

High level of plasmatic viral load which is proportional to HIV genital shedding is observed during early HIV infection resulting in individual being highly infectious during this stage compared to the chronic stage of the infection [7]. The peak of plasmatic viral load seems to occur around 17 days after infection [7] and the mean duration of high viral load before the set point is estimated around 76 days [8]. The viral load during AHI peaks at about 6.5 log₁₀ copies per mm [7,9] and the set point is approximately around 4 log₁₀ [8-10]. There is a direct correlation observed between HIV- 1 cervical and plasmatic viral load levels during early infection and the mean cervical set point is at around 1.64 log₁₀ copies per swab, occurring at around 174 days after infection [10].

To assess the proportion of HIV infections attributable to the early stage on the assumption of high risk transmission due to high viral load observed during this stage; we identified studies based on the mathematical modelling approach conducted in the SSA region, and analysed their findings. It results in general that early stage of HIV is responsible for a substantial number of HIV transmission in the region. For instance, HIV transmission attributable to primary stage was found to be 26 times higher compared to the chronic stage [11]. Powers and colleagues [12] found that 38.4% of HIV infections were attributable to an index case being in the early stage of the infection, and Pinkerton [13] reported that as high as 89.1% of all HIV transmission events that occurred in a cohort followed up during 20 mon, happened while the index case was in the early stage with the average per act transmission probability calculated at 0.03604 in the acute stage compared to 0.00084 in the chronic stage [13]. These evidences were challenged by another study suggesting that the proportion of HIV infections attributable to early stage was overestimated in previous studies and stating that only 5.3% of HIV infections were attributable to the early stage of the infection [14]. However, the same study acknowledged that the proportion of HIV infections attributable to the early stage was dependent on the individual risk-level behavior and HIV prevention interventions [14].

Regarding the role of individual risk-level behavior, evidences show that the number of transmission occurring during the primary infection is proportional to the amount of concurrence. According to the calculations of Eaton and colleagues [15], the proportion of HIV infections attributable to the early stage was estimated between 16% and 28% depending on the amount of concurrency. They demonstrated that primary HIV in term of disease transmission can be understood only in combination with concurrent sexual partnerships and their combination may be the factor that has enabled HIV epidemic to grow in the general population [15]. One study found no dominancy across the different stages of HIV in term of contribution to the disease transmission [16]. The estimated contribution to HIV transmission in this study was 17%, 51% and 32% for acute, chronic and late stage respectively. Chronic stage contributed with more than half of all HIV transmissions because of its long duration. However, acute stage was estimated to be more contributive to HIV transmission in the context of high risk sexual behavior despite its short duration [16]. The association of acute HIV stage and sexual risk behavior were explored in other studies, and it results from these studies that the epidemic cannot be sustained in the general population without the role played by AHI and highrisk sexual behavior [17]. The proportion of HIV transmission occurring while the index case is in the acute stage depends on the biological factors, behavioral patterns and the epidemic stage [18]. Regarding the epidemic stage, Powers and colleagues [12] demonstrated that AHI can still contribute to the spread of the disease in a matured epidemic as well as in early epidemic.

Targeting high-risk sexual behavior during acute HIV stage was also explored with promising results. In this regard, we identified three studies demonstrating that sustained behavior change after AHI diagnosis was achievable in majority of participants with either behavioral motivational counseling interventions, or brief education targeting risk reduction behavior [19-21]. In contrast, only one study found that the majority of participants surveyed failed to demonstrate good understanding of AHI including the notion of high infectivity thereof, in spite of information imparted to them several times in plain, no-scientific language supported by visual aid material [22].

Clinical manifestations and the risk-score algorithm for screening

Acute HIV infection is frequent in SSA. The lowest prevalence found were 0.1%, 95% CI (0.258%-0.002%) in a cohort from all hospital admissions in South Africa, and 0.21%, 95% CI (0.03%- 0.40%) in a study involving pregnant women with a negative HIV antibody test in Malawi [23,24]. The prevalence of approximately 1% was found in many other studies [25-29]. In malaria endemic area AHI is most often mistaken for malaria. According to Yeatman et al. [30], 46% of women with early HIV infection sought medical care for what they thought to be malaria.

Symptoms and signs accompanying AHI lack specificity and are present in a wide range of other morbidities [31]. Some studies have investigated clinical manifestations of AHI in SSA. More than half of women diagnosed with AHI in South Africa reported one or more signs or symptoms such as: rash, sore throat, weight loss, genital ulcer, and vaginal discharge [32]. Younger age of less than 25 yrs was associated with AHI in the same study, and the specificity and likelihood ratio of AHI increased when more of these signs and/or symptoms coexisted in one patient [32]. In addition, unexplained fever, fatigue, swelling of inguinal lymph nodes was also found to be associated with early HIV infection in women from Zimbabwe [33]. Whereas in Uganda age less than 30 years, fever, STI, diarrhea, body aches and the history of multiple sexual partners were found to be predictive of AHI [29]. However, in another study conducted in South Africa; the number of lifetime sexual partners and frequency of sexual intercourses in the last 30 days before diagnosis were the most factors found to be associated with AHI [34].

Lack of specific signs and symptoms for AHI prompted the development of the risk-score algorithm for screening in 2007. According to this algorithm, one point is assigned in the presence of each of the following: fever, body ache, and more than one sexual partner in the previous two months. Two points are assigned in the presence of each of the following: diarrhea and genital ulcer disease. Four points are assigned in the case of a discordant rapid HIV antibody test. The cut-off score of two points is supposed to detect 95.2% of AHI cases [35].

The performance of the risk-score was assessed in three studies conducted in SSA. In Malawi; the risk-score algorithm was sensitive at 71% and specific at 73% in screening patients with AHI [36]. This specificity was lower (54%) among patients recruited at STI clinics with nearly half of the participants (46.4%) meeting the threshold of two points compared to patients recruited at HTC clinics in whom the score demonstrated better performance with the sensitivity of 73%, the specificity of 89% with only 11.7% of participants meeting the threshold score of two points [36]. The risk-score algorithm of at least two points had good performance in Kilifi (Kenya) and Lilongwe (Malawi), fair performance was observed in Mombasa (Kenya) whereas, and the risk-score algorithm had poor performance in Durban (South Africa) [37]. Finally, Wahome and colleagues [38] confirmed in their study the importance of fever, diarrhea and a serodiscordant rapid HIV test for the identification of early HIV infection in African population. The same study also demonstrated that targeted screening for early HIV infection in men who have sex with men could be performed with a limited set of characteristics including age younger than 30 yrs, fever, diarrhea, fatigue, any symptomatic STD, and discordant rapid serological HIV test [38].

Point-of-Care diagnostic test for AHI

The above-given evidences have enlightened the need for diagnosing AHI at the POC in SSA. Hence some studies have attempted unsuccessfully to demonstrate in practice the theoretical possibility of the rapid fourth-generation test which can detect the HIV-specific antigen in addition to HIV-specific antibodies. For instance, the sensitivity and specificity of the p24 antigen component of the test were inadequate for widespread use to diagnose AHI in Malawi [39]. Similar results were found in Zambia whereby less than 2% of the cases antigen positive HIV infections were detected by the rapid fourth-generation test [40]. In addition, a national household survey conducted in Swaziland concluded that the rapid fourth-generation test failed to identify any true AHI, rather all the Ag+/Ab- identified by the test were falsely positive for AHI [41].

Discussion

Although one study challenged the high proportion of HIV infection attributable to AHI in SSA, most of the studies based on mathematical modelling approach examined in this review demonstrate that the early stage of the infection is associated with a substantial number of new HIV infections ranging between 16% and 38% of all HIV incidence cases. The number of new infections resulting from the index case being in the early stage is influenced by factors such as the stage of the epidemic in the society and the individual risk-level behavior. Combination of primary HIV infection and concurrent sexual partnerships, especially when new sexual partnerships are formed quickly may posit the high spread of HIV infection in region with generalised epidemic, but also in the context of concentrated epidemic [42-46]. We identified the opportunity for behavior change intervention coupled with routine screening for AHI provided by three studies with only one study rejecting this opportunity. Failure to screen and diagnose AHI in SSA constitutes a missed opportunity for behavioral and biomedical combination strategies for HIV prevention [47-49].

The clinical picture of AHI is vague and non-specific in SSA as it is elsewhere across the world [50-52]. This situation underpins the need for a risk-score algorithm for early HIV infection screening in the context of SSA. The need for a risk-score algorithm for AHI screening was also expressed in the USA in order to maximize the opportunity for targeting those most at risk [3]. Screening for AHI offers opportunity for early linkage to care and treatment with benefits ranging from immune system preservation to decrease onward transmission of HIV [53].

Both pooled NAT and fourth-generation HIV EIAs provide an increase yield for AHI diagnosis [54,55]. However, these assays are laboratory-based and not feasible at large scale in SSA [39]. Therefore, a rapid POC, cost-effective diagnostic test for AHI is highly desired in SSA [56]. In this regards, we identified studies that have investigated the practicability of the HIV rapid fourth generation EIA at POC in SSA which concluded in the nonsuitability thereof. None study assessing the practicability of the POC NAT technology for AHI diagnosis in SSA was identified. Given the role played by AHI in the spread of the infection [57,58], continuous efforts are needed to close the gap of behavioral and biomedical combination strategies for HIV prevention in the early stage of the infection in SSA. In the meantime, clinicians should be aware of common signs and symptoms and how to screen for AHI especially in high-risk group population. Patients screening positive for AHI should have their risk-level behavior assessed followed by risk-behavior reduction interventions with appropriate follow-ups in order to diagnose HIV at the earlier stage, and ensure linkage into care which results in immune preservation, prevention of morbidity and mortality in addition to the prevention of further transmission of HIV infection to other sexual partners.

In summary, 5% (for some) and 38% (for others) of all new HIV infections occurring in SSA are attributable to the index cases being in the acute stage of the infection. Concurrent sexual partnerships associated with early stage of the infections are associated factors for high rate of HIV transmission. AHI is common in SSA and most patients seek healthcare for AHI syndrome which is mistaken for other conditions such as malaria. A risk-score algorithm has been developed for targeting and screening those most at risk of AHI. However, the unavailability of a POC diagnostic test for AHI limits its application in SSA. Continuous efforts are needed to develop a suitable POC diagnostic tool for AHI in the region. In the meantime, clinicians should initiate behavioral intervention and appropriate follow-ups for patients screening positive for AHI in order to minimize new HIV cases linked to the early stage of the infection.

Limitation

Only online published primary papers conducted in SSA between 2007 and 2017 were considered for this review. Relevant information regarding AHI in SSA contained elsewhere may be omitted.

References

1. Suthar AB, Granich RM, Kato M, Nsanzimana S, Montaner JS, et al. (2015)  Programmatic implications of acute and early HIV infection. J Infect Dis9: 1351-1360.
2. Branson B.M (2015) Updates and challenges: When regulatory caution and public health imperatives collides. Curr HIV/AIDS Rep 12: 117-126.
3. Steinberg M, Cook DA, Gilbert M, Krajden M, Haag D, et al. (2011) Towards targeted screening for acute HIV infection in British Columbia. J Int AIDS Soc 14: 39.
4. Pilcher CD, Tien HC, Eron JJ Jr, Vernazza PL, Leu SY, et al. (2004) Brief but efficient: Acute HIV infection and the sexual transmission of HIV. J Infect Dis 189: 1785-1792.
5. Herout S, Mandorfer M, Breitenecker F, Reiberger T, Grabmeier-Pfistershammer K, et al. (2016) Impact of early initiation of antiretroviral therapy in patients with acute HIV infection in Vienna, Austria. PLoS One 11: e0152910.
6. Rutstein SE, Ananworanich J, Fidler S, Johnson C, Sanders EJ, et al. (2017) Clinical and public health implications of acute and early HIV detection and treatment: a scoping review. J Int AIDS Soc 20: 21579.
7. Pilcher CD, Joaki G, Hoffman IF, Martinson FE, Mapanje C, et al. (2007) Amplified transmission of HIV-1: comparison of HIV-1 concentrations in semen and blood during acute and chronic infection. AIDS 21: 1723-1730.
8. Charurat M, Nasidi A, Delaney K, Saidu A, Croxton T, et al. (2012) Characterization of acute HIV-1 infection in high-risk Nigerian populations. J Infect Dis 205: 1239-1247.
9. Novitsky V, Woldegabriel E, Kebaabetswe L, Rossenkhan R, Mlotshwa B, et al. (1999) Viral load and CD4+ T-Cell dynamics in primary HIV-1 subtype C infection. J Acquir Immune Defic Syndr 50: 65-76.
10. Morrison CS, Demers K, Kwok C, Bulime S, Rinaldi A, et al. (2010) Plasma and cervical viral loads among Ugandan and Zimbabwean women during acute and early HIV-1 infection. AIDS 24: 573-582.
11. Hollingsworth TD, Anderson RM, Fraser C (2008) HIV-1 Transmission, by stage of infection. J Infect Dis 198: 687-693.
12.  Powers KA, Ghani AC, Miller WC, Hoffman IF, Pettifor AE, et al. (2011) The role of Acute and Early HIV Infection in the spread of HIV-1 in Lilongwe, Malawi: Implications for “Test and Treat” and other transmission prevention strategies. Lancet 378: 256-268.
13. Pinkerton SD (2008) Probability of HIV transmission during acute infection in Rakai, Uganda. AIDS Behav 12: 677-684.
14. Bellan SE, Dushoff J, Galvani AP, Meyers LA (2015) Reassessment of HIV-1 acute phase infectivity: Accounting for heterogeneity and study design with simulated cohorts. PLoS Med 12: e1001801.
15. Eaton JW, Hallett TB, Garnett GP (2011) Concurrent sexual partnerships and primary HIV infection: A critical interaction. AIDS Behav 15: 687-692.
16. Abu-Raddad LJ, Longini IM Jr (2008) No HIV stage is dominant in driving the HIV epidemic in Sub-Saharan Africa. AIDS, 22: 1055-1061.
17. Goodreau SM, Cassels S, Kasprzyk D, Montaño DE, Greek A, et al. (2012) Concurrent partnerships, acute infection and HIV epidemic dynamics among young adults in Zimbabwe. AIDS Behav 16: 312-322.
18. Eaton JW, Hallett TB (2014) Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence. Proceedings of the National Academy of Sciences of the United States of America 111: 16202-7.
19. Pettifor A, MacPhail C, Corneli A, Sibeko J, Kamanga G, et al. (2011) Continued high risk sexual behavior following diagnosis with acute HIV infection in South Africa and Malawi: Implications for prevention. AIDS Behav 15: 1243-1250.
20. Corneli A, Pettifor A, Kamanga G, Golin C, McKenna K, et al. (2014) HPTN062: A feasibility and acceptability pilot intervention to reduce HIV transmission risk behaviors among individuals with acute and early HIV infection in Lilongwe, Malawi. AIDS Behav 18: 1785-1800. 
21. Pettifor A, Corneli A, Kamanga G, McKenna K, Rosenberg NE, et al. (2015) HPTN 062: A pilot randomized controlled trial exploring the effect of a motivational-interviewing intervention on sexual behavior among individuals with acute HIV infection in Lilongwe, Malawi. PLoS One 10: e0124452.
22. Wolpaw BJ, Mathews C, Mtshizana Y, Chopra M, Hardie D, et al. (2014) Patient experiences following acute HIV infection diagnosis and counseling in South Africa. PLoS One. 9: e105459.
23. Gous N, Scott L, Perovic O, Venter F, Stevens W (2010) Should South Africa be performing nucleic acid testing on HIV enzyme-linked immunosorbent assay-negative samples? J Virol 48: 3407-3409.
24. Gay CL, Mwapasa V, Murdoch DM, Kwiek JJ, Fiscus SA, et al. (2010) Acute hiv infection among pregnant women in Malawi. Diagn Microbiol Infect Dis 66: 356-360.
25. Mayaphi SH, Martin DJ, Quinn TC, Laeyendecker O, Olorunju SA, et al. (2016) Detection of acute and early HIV-1 infections in an HIV hyper-endemic area with limited resources. PLoS One 11: e0164943.
26. Kharsany A, Hancock N, Frohlich J, Humphries H, Abdool Karim S, et al. (2010) Screening for ‘window-period’ acute HIV infection among pregnant women in rural South Africa. HIV Med 11: 661-665.
27. Basset IV, Chetty S, Giddy J, Reddy S, Bishop K, et al. (2011) Screening for acute HIV infection in South Africa: Finding acute and chronic disease. HIV Med 12: 46-53.
28. Bebell LM, Pilcher CD, Dorsey G, Havlir D, Kamya MR, et al. (2010) Acute HIV-1 infection is highly prevalent in Ugandan adults with suspected malaria. AIDS 24: 1945-1952.
29. Sanders EJ, Mugo P, Prins HA, Wahome E, Thiong'o AN, et al. (2014) Acute HIV-1 infection is as common as malaria in young febrile adults seeking care in coastal Kenya. AIDS 28: 1357-1363.
30. Yeatman SE, Hoffman RM, Chilungo A, Lungu SR, Namadingo HC, et al. (2015) Health-seeking behavior and symptoms associated with early HIV infection: Results from a population-based cohort in southern Malawi. J Acquir Immune Defic Syndr 69: 126-130.
31. Novitsky V, Woldegabriel E, Wester C, McDonald E, Rossenkhan R, et al. (2008) Identification of primary HIV-1C infection in Botswana. AIDS Care 20: 806-811.
32. Mlisana K, Sobieszczyk M, Werner L, Feinstein A, van Loggerenberg F, et al. (2013) Challenges of diagnosing acute HIV-1 subtype C infection in African women: Performance of a clinical algorithm and the need for point-of-care nucleic-acid based testing. PLoS One 8: e62928.
33. Lemonovich TL, Watkins RR, Morrison CS,  Kwok C,  Chipato T,  et al.  (2015) Differences in clinical manifestations of acute and early HIV-1 infection between HIV-1 subtypes in African women. J Int Assoc Provid AIDS Care 14: 415-422.
34. Dong KL, Moodley A, Kwon DS, Ghebremichael MS, Dong M, et al. (2018) Detection and treatment of Fiebig stage I HIV-1 infection in young at risk women in South Africa: a prospective cohort study. Lancet HIV 5: e35-44.
35. Powers KA, Miller WC, Pilcher CD, Pilcher CD, Mapanje C, et al. (2007) Improved detection of acute HIV-1 infection in sub-Saharan Africa: development of a risk score algorithm. AIDS 21: 2237-2242.
36. Rutstein SE, Pettifor AE, Phiri S, Kamanga G, Hoffman IF, et al. (2016) Incorporating acute HIV screening into routine HIV testing at sexually transmitted infection clinics, and HIV testing and counseling centers in Lilongwe, Malawi. J Acquir Immune Defic Syndr 71: 272-280.
37. Sanders EJ, Wahome E, Powers KA, Werner L, Fegan G, et al. (2015) Targeted screening of at-risk adults for acute HIV-1 infection in sub-Saharan Africa. AIDS 29: 221-230.
38. Wahome E, Fegan G, Okuku HS, Mugo P, Price MA, et al. (2013) Evaluation of an empiric risk screening score to identify acute and early HIV-1 infection among MSM in Coastal Kenya. AIDS 27: 2163-2166.
39. Rosenberg NE, Kamanga G, Phiri S, Nsona D, Pettifor A, et al. (2012) Detection of acute HIV infection: A field evaluation of the determine® HIV-1/2 Ag/Ab combo test. J Infect Dis 205: 528-534.
40. Kilembe W, Keeling M, Karita E, Lakhi S, Chetty P, et al. (2012) Failure of a novel, rapid antigen and antibody combination test to detect antigen-positive HIV infection in African adults with early HIV infection. PLoS One. 7: e37154.
41. Duong YT, Mavengere Y, Patel H, Moore C, Manjengwa J, et al. (2014) Poor performance of the determine HIV-1/2 Ag/Ab combo fourth-generation rapid test for detection of acute infections in a national household survey in Swaziland. J Clin Microbiol 52: 3743-3748.
42. Pinkerton SD (2007) How many sexually-acquired HIV infections in the USA are due to acute-phase HIV transmission? AIDS 21: 1625-1629.
43. Cohen MS, Shaw GM, McMichael AJ, Haynes BF (2011) Acute HIV-1 infection. N Engl J Med 364: 1943-1954.
44. Knopf A, Agot K, Sidle J, Naanyu V, Morris M (2014) This is the medicine: “A Kenyan community responds to a sexual concurrency reduction intervention. Soc Sci Med 108: 175-184.
45. Beyrer C, Sullivan P, Sanchez J, Baral SD, Collins C, et al. (2013) The increase in global HIV epidemics in MSM. AIDS 27: 2665-2678.
46. Miller WC, Rosenberg NE, Rutstein SE, Powers KA (2010) The Role of acute and early HIV infection in the sexual transmission of HIV. Curr Opin HIV AIDS 5: 277-282.
47. Rotham RE (2004) Current centers for disease control and prevention guidelines for HIV counseling, testing, and referral: Critical role of and a call to action for emergency physicians. Ann Emerg Med 44: 31-42.
48. Bekker LG, Beyrer C, Quinn TC (2012) Behavioral and biomedical combination strategies for HIV prevention. Cold Spring Harb Perspect Med 2: a007435.
49. Joint United Nations Programme on HIV/AIDS (2010) UNAIDS combination HIV prevention: Tailoring and coordinating biomedical, behavioral and structural strategies to reduce new HIV infections. Geneva.
50. Hsu DT, Ruf M, O'Shea S, Costelloe S, Peck J, et al. (2013) Diagnosing HIV infection in patients presenting with glandular fever-like illness in primary care: Are we missing primary HIV infection? HIV Med 14: 60-63.
51. O’Brien M, Markowitz M (2012) Should we treat acute HIV infection? Curr HIV/AIDS Rep 9: 101-110.
52. Robb ML, Eller LA, Kibuuka H, Rono K, Maganga L, et al. (2016) Prospective study of acute HIV-1 infection in adults in East Africa and Thailand. New England J Med 374: 2120-2130.
53. Martin EG, Salaru G, Mohammed D, Coombs RW, Paul SM, et al. (2013) Finding those at risk: Acute HIV Infection in Newark, NJ. J Clin Virol 58: 24-28.
54. Krajden M, Cook D, Mak A, Chu K, Chahil N, et al. (2014) Pooled nucleic acid testing increases the diagnostic yield of acute HIV infection in a high-risk population compared to 3rd and 4th generation HIV enzyme immunoassays. J Clin Virol 61: 132-137.
55. Eshleman SH, Khaki L, Laeyendecker O, Piwowar-Manning E, Johnson-Lewis L, et al. (2009) Detection of individuals with acute HIV-1 infection using the ARCHITECT® HIV Ag/Ab combo assay. J Acquir Immune Defic Syndr 52: 121-124.
56. Rudolph DL, Sullivan V, Owen SM, Curtis KA (2015) Detection of acute HIV-1 infection by RT-LAMP. PLoS One 10: e0126609.
57. Jain V, Hartogensis W, Bacchetti P, Hunt PW, Hatano H, et al. (2013) Antiretroviral Therapy Initiated Within 6 Months of HIV Infection Is Associated With Lower T-Cell Activation and Smaller HIV Reservoir Size. J Infect Dis 208: 1202-1211.
58. White PJ, Fox J, Weber J, Fidler S, Ward H (2014) How many HIV infections may be averted by targeting primary infection in men who have sex with men? Quantification of changes intransmission-risk behavior, using an individual-based model. J Infect Dis 210: 594-599.