Antivirus effectiveness of ivermectin on dengue virus type 2 in Aedes albopictus
Authors: Xing-Ya Pang
Yi Zhang
Yin Han
Tie-Long Xu
Bin Zheng
Xiao-Nong Zhou
Wei Liu
Journal: PLoS Neglected Tropical Diseases (2018)
Discipline: IMMUNOLOGY
Keywords: Dengue fever; vector control; ivermectin; DENV-2; Aedes albopictus
Affiliations: National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, and National Center for Tropical Diseases Research, Shanghai, the People's Republic of China., Key Laboratory of Parasite and Vector Biology, Ministry of Public Health, and WHO Collaborating Centre for Tropical Diseases, Shanghai, the People's Republic of China., Nanchang Customs District, and Jiangxi International Travel Healthcare Center, Nanchang, the People's Republic of China.

Abstract:  Background: Dengue fever is the most rapidly spreading mosquito-borne viral disease over the past 50 years, with a 30-fold increase in global incidence. Dengue vector control is a key component for the dengue control strategy, since no absolutely effective vaccine or drug is available yet. However, the rapid rise and spread of mosquito insecticide resistance have become major threats to the efficiency of insecticide-based vector control activities. Thus, innovative vector control tools are badly needed. This study aims to confirm the antivirus effectiveness of ivermectin on dengue virus type 2 (DENV-2) in Aedes albopictus (Skuse, 1894), then to explore its potential use in the combating to the dengue epidemics. Methods: Aedes albopictus were first infected with DENV-2 in human whole blood, and at the fourth day after infectious blood feeding, they were divided into eight groups. Seven of them were held for six days with access to 0, 2, 4, 8, 16, 32 and 64 ng/ml ivermectin, respectively, and the last one was set as a historical control group, which was stored at -80°C until being detected at the same time with the other groups. Each mosquito was detected using real-time fluorescent RT-PCR kit. DENV-2 RNA concentration (copies/ml) and infection rate in each group were compared. Results: Both of quantitatively and qualitatively inhibiting effects of ivermectin have been detected in this study. Generally, DENV-2 replicated well in Aedes albopictus without ivermectin intervention, whose virus loads exhibited significantly higher when the mosquitoes were holding from 4 days to 10 days after infectious blood feeding. In contrast, with the treatment of ivermectin, the infection rate was reduced by as much as 49.63%. The regression equation between infection rates (Y2) and ivermectin concentration log2 values (X2) was obtained as Y2 = 91.41-7.21*X2 with R2 = 0.89. Conclusion: Ivermectin can directly or indirectly inhibit DENV-2 multiplication in Aedes albopictus. Moreover, the actual concentration for application in zooprophylaxis needs to be confirmed in the further field trials. 

Retracted: No

PubPeer comments:
 At the outset I would like to indicate that I am posting on here as a last resort, not a first step. I raised all the concerns in my comment below with the corresponding author by email in April of 2020, one year ago. I did not receive a response. The authors institution does not appear to have a complaints process or appropriate contact. I then raised similar concerns with the journal in May of 2020, 11 months ago. I understood my concerns were being investigated however in recent months I have not received any contact despite asking for an update. Attached below is a copy of my email to the editor. From: Kyle Sheldrick [redacted] Sent: 5 4 2020 12:11 AM To: plosntds@plos.org Subject: Concerns about data [redacted] in paper on ivermectin, no response received from author.  Dear Editor I am writing to you to raise concerns about the integrity of data in a recent paper in your journal. I have contacted the corresponding author last month and received no response. The institution (Chinese Centre for Disease Control) does not have any complaints or notification process on their website. As such I have decided to bring it to your attention as the publisher. The article is https: journals.plos.org plosntds article?id=10.1371 journal.pntd.0006934 My concerns relate especially to the data provided in table 1, which is implausibly distributed. In short the authors claim to have created 24 separate cohorts of mosquito fed on dengue infected blood, consisting of 3 replicates each of 8 different dosing regimens. The thing that drew my attention was that despite 24 cohorts of relatively small n there are no outliers. In short, the distribution of results (frequencies within groups) in table 1 is far more perfect than the fixed nature of binomial distribution would suggest is plausible. Of the 24 cohorts (8 treatment groups, each tested in 3 replicates of approximately n=20 mosquitoes), 23 out of 24 cohorts reported results that were  perfect , that is, less than one mosquito from the overall average response rate for that dose. Obviously the overall by-dose average is not an independent measure (being partially derived from those same replicates cohorts) so that s perhaps an unfair way of assessing things, so I have taken the liberty of calculating the average response rate for that dosing regime for each cohort with the cohort under investigation removed (I have included this table at the end of the email). On this basis, all 24 cohorts came within 9% of the average frequency of infection for the remaining replicates of that dose (i.e. with the cohort in question removed from the average). The likelihood of results this perfect (even assuming the underlying drug effect is real and exactly as calculated in all cohorts) can be calculated as the product of the 24 probabilities of each cohort falling within this range. This gives us a probability of about 7x10^-5, or 7 in 100,000 of the data being distributed so perfectly if the experiment was conducted as described, even assuming the underlying effect of the drug was as measured. On a similar basis 23 out of 24 cohorts came within 6.1% of the  true average (i.e. with the cohort in question removed from the average). The likelihood of results this perfect (again, even assuming the underlying drug effect is real and exactly as calculated in all cohorts) can be calculated as the sum of the 25 scenario probabilities (i.e. the sum of the product of probabilities of all cohorts being within target range, and the sum of similar calculations where each of the 24 probabilities was substituted with its compliment alternate probability of that single cohort falling outside the target range). This gives us a probability of about 1.6x10^-6, or less than 2 in 1 million of the data being distributed so perfectly if the experiment was conducted as described, again even assuming the underlying effect of the drug was as measured. Put more simply, it s just implausible to conduct 24 cohorts of n =~20 and have no outliers, much less to get so close to the exact right answer 23 out of 24 times. Please let me know how you choose to proceed. Yours sincerely , 
 Published in _RetractionWatch_ on January 19, 2022: https: retractionwatch.com 2022 01 19 how-an-ivermectin-study-that-didnt-mention-covid-19-fell-under-scrutiny ,