{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T23:37:09Z","timestamp":1792885029512,"version":"4.5.0"},"update-to":[{"DOI":"10.12688\/f1000research.19859.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T00:00:00Z","timestamp":1591833600000}}],"reference-count":34,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T00:00:00Z","timestamp":1591833600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000030","name":"Centers for Disease Control and Prevention","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000030","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["OPP1099252"],"award-info":[{"award-number":["OPP1099252"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006506","name":"Brazilian Ministry of Health","doi-asserted-by":"crossref","award":["TED 09\/2016"],"award-info":[{"award-number":["TED 09\/2016"]}],"id":[{"id":"10.13039\/501100006506","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"\n Background:<\/ns3:bold>\n Rio de Janeiro and Niter\u00f3i are neighbouring cities in southeastern Brazil which experience large dengue epidemics every 2 to 5 years, with >100,000 cases notified in epidemic years. Costs of vector control and direct and indirect costs due to the\n Aedes<\/ns3:italic>\n -borne diseases dengue, chikungunya and Zika were estimated to total $650 million USD in 2016, but traditional vector control strategies have not been effective in preventing mosquito-borne disease outbreaks. The\n Wolbachia<\/ns3:italic>\n method is a novel and self-sustaining approach for the biological control of\n Aedes<\/ns3:italic>\n -borne diseases, in which the transmission potential of\n Aedes aegypti<\/ns3:italic>\n mosquitoes is reduced by stably transfecting them with the\n Wolbachia<\/ns3:italic>\n bacterium (\n w<\/ns3:italic>\n Mel strain). This paper describes a study protocol for evaluating the effect of large-scale non-randomised releases of\n Wolbachia\u00ad<\/ns3:italic>\n -infected mosquitoes on the incidence of dengue, Zika and chikungunya in the two cities of Niter\u00f3i and Rio de Janeiro. This follows a lead-in period since 2014 involving intensive community engagement, regulatory and public approval, entomological surveys, and small-scale pilot releases.\n <\/ns3:p>\n \n Method:<\/ns3:bold>\n The\n Wolbachia<\/ns3:italic>\n releases during 2017-2019 covered a combined area of 170 km\n 2<\/ns3:sup>\n with a resident population of 1.2 million, across Niter\u00f3i and Rio de Janeiro. Untreated areas with comparable historical dengue profiles and demographic characteristics have been identified\n a priori<\/ns3:italic>\n as comparative control areas in each city. The proposed pragmatic epidemiological approach combines a controlled interrupted time series analysis of routinely notified suspected and laboratory-confirmed dengue and chikungunya cases, together with monitoring of\n Aedes<\/ns3:italic>\n -borne disease activity utilising outbreak signals routinely used in public health disease surveillance.\n <\/ns3:p>\n \n Discussion:<\/ns3:bold>\n If the current project is successful, this model for control of mosquito-borne disease through\n Wolbachia<\/ns3:italic>\n releases can be expanded nationally and regionally.\n <\/ns3:p>","DOI":"10.12688\/f1000research.19859.2","type":"journal-article","created":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T10:10:11Z","timestamp":1591870211000},"page":"1328","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["The impact of large-scale deployment of Wolbachia mosquitoes on dengue and other Aedes-borne diseases in Rio de Janeiro and Niter\u00f3i, Brazil: study protocol for a controlled interrupted time series analysis using routine disease surveillance data"],"prefix":"10.12688","volume":"8","author":[{"given":"Betina","family":"Durovni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7360-6490","authenticated-orcid":false,"given":"Valeria","family":"Saraceni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana","family":"Eppinghaus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thais I.S.","family":"Riback","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luciano A.","family":"Moreira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas P.","family":"Jewell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6316-6548","authenticated-orcid":false,"given":"Suzanne M.","family":"Dufault","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott L.","family":"O'Neill","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cameron P.","family":"Simmons","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephanie K.","family":"Tanamas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0485-5826","authenticated-orcid":false,"given":"Katherine L.","family":"Anders","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2560","published-online":{"date-parts":[[2020,6,11]]},"reference":[{"key":"ref-1","doi-asserted-by":"publisher","first-page":"504-7","DOI":"10.1038\/nature12060","article-title":"The global distribution and burden of dengue.","volume":"496","author":"S Bhatt","year":"2013","journal-title":"Nature."},{"key":"ref-2","doi-asserted-by":"publisher","first-page":"584-93","DOI":"10.4269\/ajtmh.2012.11-0770","article-title":"The history of dengue outbreaks in the Americas.","volume":"87","author":"O Brathwaite Dick","year":"2012","journal-title":"Am J Trop Med Hyg."},{"key":"ref-3","doi-asserted-by":"publisher","first-page":"321873","DOI":"10.1155\/2015\/321873","article-title":"Epidemiological Scenario of Dengue in Brazil.","volume":"2015","author":"R Fares","year":"2015","journal-title":"Biomed Res Int."},{"key":"ref-4","doi-asserted-by":"publisher","first-page":"48-53","DOI":"10.3201\/eid1101.031091","article-title":"Dengue and dengue hemorrhagic fever, Brazil, 1981-2002.","volume":"11","author":"J Siqueira","year":"2005","journal-title":"Emerg Infect Dis."},{"key":"ref-5","doi-asserted-by":"publisher","first-page":"e0004636","DOI":"10.1371\/journal.pntd.0004636","article-title":"Zika Virus Outbreak in Rio de Janeiro, Brazil: Clinical Characterization, Epidemiological and Virological Aspects.","volume":"10","author":"P Brasil","year":"2016","journal-title":"PLoS Negl Trop Dis."},{"key":"ref-6","doi-asserted-by":"publisher","first-page":"951-8","DOI":"10.1056\/NEJMoa1600651","article-title":"Zika Virus Associated with Microcephaly.","volume":"374","author":"J Mlakar","year":"2016","journal-title":"N Engl J Med."},{"key":"ref-7","article-title":"Boletins epidemiol\u00f3gicos","year":"2018"},{"key":"ref-8","article-title":"Monitoramento do Per\u00edodo Sazonal da Febre Amarela Brasil - 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Hyg."}],"container-title":["F1000Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2\/iparadigms","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T06:10:13Z","timestamp":1608617413000},"score":1,"resource":{"primary":{"URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,11]]},"references-count":34,"URL":"https:\/\/doi.org\/10.12688\/f1000research.19859.2","relation":{"has-review":[{"id-type":"doi","id":"10.5256\/f1000research.27081.r74998","asserted-by":"subject"},{"id-type":"doi","id":"10.5256\/f1000research.27081.r74998","asserted-by":"object"}]},"ISSN":["2046-1402"],"issn-type":[{"value":"2046-1402","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,11]]},"assertion":[{"value":"Indexed","URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2#article-reports","order":0,"name":"referee-status","label":"Referee status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.5256\/f1000research.21787.r51960, Liz Turner, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA, 07 Nov 2019, version 1, 1 approved, 1 approved with reservations","URL":"https:\/\/f1000research.com\/articles\/8-1328\/v1#referee-response-51960","order":0,"name":"referee-response-51960","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"Katherine ANDERS<\/b>; \nPosted: 01 Jun 2020<\/i>; \nMain comments<\/b> \n1.    I have a desire to see more justification for why randomisation was not possible. The difficulties of randomisation in this setting are mostly described but, as you\u2019ll see from my more detailed comments below, it\u2019s not absolutely convincing that randomisation would not have been possible here, even within the interrupted time series design.<\/b> We agree with the reviewer that randomisation could be combined with ITS, and in principle this could be a stronger design. However randomisation of the deployment (either by random allocation of parallel treated and untreated areas, or by randomising the sequence of staged deployments) would have necessitated the study site being divided up into a large number of spatial units for randomisation. Logistically, this would have made the community engagement and deployment activities infeasible within the funding and time constraints of the project, and in the context of the large and complex urban setting. Intensive stakeholder and community engagement, and deployment planning, could only have commenced after the randomisation process had occurred and the intervention areas were determined. Field activities would then have had to be conducted in a spatially fragmented way, complicating the stakeholder and community engagement and the deployment logistics and inevitably lengthening time frames. Smaller non-contiguous release areas interspersed with untreated areas would also have greatly increased the potential for contamination between treatment arms from both mosquito movement and human movement, thereby diluting the observable intervention effect. Please see our responses to comments #7 and #11 below, and Reviewer 2 comment #3. \n2.    Because the measurement of incidence of the arboviruses of interest is mostly through surveillance data and it may be difficult to blind communities to the use of Wolbachia, how can it be determined that in the treatment zones post-Wolbachia release any smaller incidence is not just related to the fact that there is lower reporting as community members expect the incidence of those viruses to go down? I have a big concern about the possibility of differential assessment of outcomes in treated and control zones. Can the authors elaborate on this in relevant places in the text?<\/b> It is plausible that community awareness could alter health-care seeking behaviour, or diagnostic \/ reporting practices, in areas where Wolbachia releases have been conducted. However we find it unlikely that this could lead to a large and sustained difference in dengue case notifications across two cities as large and complex as these, where the total intervention area exceeds 120km2 and 1 million inhabitants. Dengue (and chikungunya and Zika) is a notifiable disease, so there remains a requirement for health care providers to report any suspected cases meeting the standard case definition. We have included a discussion of this as potential limitation, in the fourth paragraph of the discussion. From the beginning of the project's engagement with communities, all messaging has reinforced the continued importance of routine activities related to arbovirus surveillance and care.  \nMinor comments 3.    It could help the reader if when \u2018dengue, chikungunya and Zika\u2019 are first mentioned in the abstract, they are also named as arboviruses i.e. to help readers not necessarily familiar with them to be certain that all three fall in to this class of viruses.<\/b> Since the three arboviruses of interest are specifically those vectored by Aedes mosquitoes, for greater clarity we have replaced \u2018arboviruses\u2019 with \u2018Aedes-borne viruses\u2019 in most instances throughout the abstract and article text, including in the manuscript title. Elsewhere we have replaced \u2018arboviral disease\u2019 with the more intuitive term \u2018mosquito-borne disease\u2019. In the last sentence of paragraph one, it is made clear that the term \u2018arbovirus\u2019 encompasses dengue, chikungunya, Zika, yellow fever and Mayaro viruses, and that these are specifically Aedes-borne arboviruses. \n4.    Based on the title referring to arboviruses, as a reader I was expecting the first sentence or so to at least mention arbovirus. Would it be possible to do so? This could be achieved very easily by saying something like \u201cThe global incidence of the arbovirus dengue has increased dramatically in recent decades\u201d.<\/b> As above, the manuscript title has been adjusted to replace \u2018arboviral disease\u2019 with \u2018Aedes-borne disease\u2019 to improve clarity for the reader. The first sentence introduces dengue (the disease) as a global public health challenge, and the last sentence of that paragraph defines dengue, chikungunya and Zika (and yellow fever and Mayaro) as Aedes-borne diseases (and arboviruses). A definition of arbovirus as meaning a mosquito-borne virus has also been added to this sentence. \n5.    In the fourth paragraph referring to yellow fever, please clarify if it is an arbovirus.<\/b> Yellow fever has been defined as an Aedes-borne arboviruses in the last sentence of the first paragraph of the introduction. \n6.    The last sentence of the sixth paragraph: \u201cLaboratory data indicate a similar reduction in the competence of Wolbachia-carrying Ae. aegypti for transmitting other viruses include ZIka, chikungunya, yellow fever and Mayaro\u201d. If all listed are arboviruses, please edit \u2018viruses\u2019 to \u2018arboviruses\u2019.<\/b> The text has been corrected as suggested. \n7.    In the ninth paragraph, I very much appreciate the rationale that there was demand for scale-up of implementation of the Wolbachia releases. I would appreciate a little more clarity on why randomization was not possible since, given that not all areas of the study will receive the treatment during the study, the scale-up argument doesn\u2019t seem sufficient to justify no randomization. I can very well imagine that there are many compelling reasons to not randomize, some of which are alluded to, and so it would help to be even clearer about this e.g. was it because of the existing partnerships and infrastructure making certain areas better for release than others? What else? Some of this is sort of implied in the text and it would be valuable to have just a few more explicit sentences regarding this.<\/b> Please see our response to Major comment #1 above. We have added text to the end of the ninth paragraph of the introduction, expanding on this justification for not randomising, as suggested. \n8.    Related to my previous comments on arboviruses, in the tenth paragraph\u2026again it could really help the reader to edit this sentence to something like \u201c\u2026three arboviruses, namely dengue, Zika and chikungunya\u2026\u201d<\/b> Consistent with our response to comment # above, we have adjusted the wording in the paragraph to refer to dengue, Zika and chikungunya as \u2018Aedes-borne diseases\u2019 or \u2018mosquito-borne diseases\u2019. \n9.    Why do the two stated objectives only relate to dengue? It will be important to make clear in the manuscript as it is strange that the overall goals are related to three arboviruses but the objectives only related to one of them.<\/b> Thank you for pointing out this inconsistency, we have corrected the wording of the aims and first objective to be inclusive of dengue, chikungunya and Zika (as the Aedes-borne diseases of interest). The second objective still relates only to dengue, as the outbreak indicators used routinely for public health purposes in Rio and Niteroi apply only to dengue outbreak monitoring. As explained under \u2018Controlled interrupted time series analysis\u2019 (3rd and 4th paragraphs, page 11), the primary endpoint for the ITS analysis will be dengue for which there is the longest historical case time series, with chikungunya and Zika analysed as secondary endpoints in the ITS. \n10.     Table 1: Are zones 1-3 in Niteroi and zones 1-3.2 in Rio the release areas? If so, please more clearly label this in the table as it is not immediately obvious to me. Perhaps add a sub-heading of \u201crelease areas\u201d above the rows where the names of the release zones are provided.<\/b> Thank you for this suggestion, we have improved the labelling of the areas in Table 1 to make clearer which are the release zones and non-release areas. Please note that we have also updated this table and Figure 2 to reflect an additional release zone in Niteroi (and the consequent reduced size of the control area). \n11.    Overall the rationale appears reasonable for the use of controlled interrupted time series but, in reference to my comments above, please look for some opportunities to be even clearer about why randomisation could not be used. An interrupted time series design could still be adopted, but one with randomisation could offer even stronger evidence.<\/b> Please see our responses to comments #1 and #7 above. Additional discussion of the justification for not randomising, and the potential benefits from the pragmatic evaluation of a large-scale contiguous release, has been added to the third paragraph of the discussion section on page 12. \n12.    \u201cIn Rio de Janeiro, two administrative areas adjacent to the release area have been designated a priori as a comparative control zone (Figure 1), based on comparable sociodemographic characteristics and synchronous historical dengue time series (Figure 2 and Table 1).\u201d I do not see any information on these SES characteristics except for population whereas I see the \u201csynchronous historical dengue time series\u201d data in Figure 2, which is really helpful. Can more info on SES be added to the appendix or is the data presented the extent of the available data? As a reader, I would want that information when judging the validity of the comparisons between treatment and control areas. <\/b> Unfortunately socio-economic data are not available aggregate to the release zones. We have now corrected this text to clarify that the comparability of the untreated control areas is demonstrated by the synchronous historical dengue time series. \n13.    Incidentally, is no historical data available on Zika and Chikungunga? If it is available, it would be really valuable to see that compared between treated and control. I see in the last paragraph of pg 6 that some such data is available so why not include it in the current manuscript?<\/b> Historical chikungunya data for the intervention areas and control areas is now included as Figure 3. \n14.    It is stated: \u201cZone-level ITS analyses will be performed 12 months after completion of releases in each zone, and each 12 months thereafter, with release zones considered \u2018treated\u2019 for the purpose of this analysis based on completion of releases, regardless of the long-term Wolbachia monitoring results.\u201d What does \u201cperformed 12 months after completion\u201d? Is it literally about the timing of running the analyses, even though data from each month will be used? The reason I ask for clarification is that on first read I thought that this meant there was a switch to only using data at 12 months after completion of the releases. Also, what is the time frame for control areas where there is no release? Please be more specific.<\/b> Yes, this is about the timing of running the analyses, ie. the intervention effect will be estimate for each zone when 12 months of post-release observations have accumulated in that zone, and repeated each 12 months thereafter (for five years) on cumulative post-release observations. And the same for the city-level analyses. The text at the end of the first paragraph under the heading \u2018Controlled interrupted time series analysis\u2019 has been edited to clarify this. There is no separate analysis for control areas, these are included in the regression model as the comparator for each individual release zone, and for the city-level analysis. This has been clarified in the text. \n15.    \u201cAggregate release area level analyses will be performed for each municipality 12 months after completion of releases in the last zone and each 12 months thereafter.\u201d What are municipalities? Please define this term when it is first introduced as I don\u2019t see this term defined elsewhere. Is it city i.e. Rio and Niteroi? If so, why not just use the same term throughout i.e. municipality or city, and only choose one of those terms?<\/b> We recognise this inconsistency may have been confusing, and have changed throughout to use \u2018city\/cities\u2019 in place of \u2018municipality\/municipalities\u2019. \n16.    Model diagnostics to be used e.g. what happens if there is even more dispersion than can be accommodated than the proposed negative binomial models?<\/b> Of the common count models, negative binomial models have the most flexible approach for handling overdispersion in count data by assuming that the variance is a quadratic function of the mean. Common causes of overdispersion can range from an excess of zero counts, unexplained heterogeneity, and\/or temporal autocorrelation. The models as proposed will be using flexible cubic splines to explain secular and temporal trends, hopefully leaving very little remaining unexplained heterogeneity. To account for any lingering heteroskedasticity or temporal autocorrelation, heteroskedasticity-robust estimation will be used for estimating variance. This has now been made explicit in the description of the Controlled interrupted time series methods. If an excess of zero counts is apparent, the proposed negative binomial model will be nested within a zero-inflated negative binomial model of the same structure. A likelihood ratio test can be performed to test model fit. This is also now described in the methods. \n17.    How will contrasts be made between the treated and control communities? As far as I can tell, this is not specified, though perhaps I\u2019m missing it? Please specific which parameters will be used to estimate the \u201ctreatment\u201d effect<\/b> The regression model will use monthly dengue case time series data for the treated area (either an individual release zone or aggregate city-level release area, as specified in the text) and the control area (one control area per city). The treatment effect will be estimated from the interaction between a binary \u2018area\u2019 variable (treated vs control) and a binary \u2018period\u2019 variable (post-Wolbachia vs pre-Wolbachia). This allow explicitly for a level change in the outcome (dengue case incidence) in both intervention and control arms in the post-intervention period, for example in a scenario where other secular events coincident with the Wolbachia deployments may have influenced dengue incidence in both intervention and control areas independent of Wolbachia. The text under \u2018Controlled interrupted time series\u2019 has been revised to clarify this. \n18.    How will the fact that the control zones are not randomized be accounted for in modelling i.e. although the set of control zones were selected to be comparable on average to those treated based on historical dengue incidence and SES, what about other factors that may be different between the treated and control zones?<\/b> Quasi-experimental designs, such as the proposed ITS analysis, aim to address the validity concerns associated with non-randomization in several ways. By using a region's historic data to inform the counterfactual outcome, the ITS analysis aims to minimize threats to internal validity. Second, by adding control regions and performing a controlled ITS, we better account for seasonal and secular influences during both the pre- and post-intervention periods. While it is true that there may be other factors associated with dengue risk that differ between treated and control zones in a non-randomised design, we make the implicit assumption in the controlled ITS that these differences are consistent throughout both the pre- and post-intervention period. Any divergence in the post-intervention period from the synchrony in dengue time series observed between intervention and control zones in the pre-intervention period is therefore assumed to represent an intervention effect. However we cannot exclude the possibility of a concurrent change in socio-demographic or ecological factors related to dengue risk, or a concurrent change in dengue control practices, between the intervention and control areas independe of the Wolbachia intervention. We have expanded on this limitation in the discussion. \n19.    Will there be a \u201cfake\u201d interruption in the series for the control areas? It doesn\u2019t seem necessary and may be problematic but would be valuable to describe explicitly what will be done in the time series modelling for the control zones.<\/b> The inclusion of the control area time series in the regression model and estimation of the intervention effect from an interaction between \u2018area\u2019 and \u2018period\u2019 effectively does allow for a \u2018fake\u2019 interruption in the series for the control area, as it allows for a step change in the control area as well as the treated area, post-intervention. The interaction parameter from which the intervention effect is estimated indicates whether there was any change in dengue incidence following the Wolbachia intervention in areas where Wolbachia releases occurred, over and above any change in dengue incidence that was observed in the untreated control area. \n20.    The discussion starts with a sentence on dengue, zika and yellow fever. Why is yellow fever not included in the outcome measures for the proposed study?<\/b> Yellow fever is not included as an endpoint for the study because there is not a history of urban yellow fever in the cities of Rio and Niteroi. The recent outbreak in Rio de Janeiro state that is mentioned early in the discussion included some urban cases, but in other parts of the state. We have removed that sentence from the first paragraph of the discussion, to avoid confusion.","URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2#referee-comment-5566","order":1,"name":"referee-comment-5566","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.21787.r57000, Adeshina I.\u00a0 Adekunle, Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Australia, 09 Dec 2019, version 1, 1 approved, 1 approved with reservations","URL":"https:\/\/f1000research.com\/articles\/8-1328\/v1#referee-response-57000","order":2,"name":"referee-response-57000","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"Katherine ANDERS<\/b>; \nPosted: 01 Jun 2020<\/i>; \nMajor comments 1.    The authors failed to indicate the strain of Wolbachia used in this study. Different strains of Wolbachia have different characteristics that enable them to invade the wild type population and establish themselves. The wMel strain was used in Townsville, Australia and was claimed to be successful. However, with climate change and variability in temperature, some Wolbachia-infected mosquitoes with different strains, include wMel, cannot maintain their Wolbachia status. Hence, even if the intervention works, an introduction of infected patients into such a population will result in an outbreak and all the gains from Wolbachia strategy would have been lost as the majority of the mosquitoes are now uninfected. <\/b> Thank you for drawing our attention to this oversight. We have now indicated the strain used (wMel) in the abstract, the sixth paragraph of the introduction, the \u2018Wolbachia release and monitoring\u2019 subheading of the Methods, and the first paragraph of the discussion. While it is true that other Wolbachia strains have been shown to have higher thermostability than wMel in the mosquito larval life stages, the effect of heatwaves on wMel Wolbachia prevalence in Wolbachia-treated areas of northern Australia has been shown to be transient (Ross et al, PLoS NTD 2020). Long-term monitoring of WMP\u2019s release sites in northern Australia and Yogyakarta, Indonesia, has demonstrated sustained high levels of Wolbachia 2 \u2013 8 years post-release. Entomological monitoring of Wolbachia prevalence in local Ae. aegypti populations in the Rio and Niteroi release areas is currently ongoing, and so will provide empirical evidence of the level to which wMel introgression is sustained over time. \n2.    Figure 1 in the manuscript shows the map of the treated and untreated zones. These are adjacent zones, especially for the treated and untreated zones. Mosquitoes movement from untreated zone to treated zone could prevent Wolbachia invasion4 and vice versa. Hence, and since this is a study that takes a few years, mosquitoes migration cannot be ruled out. Thus, the control zones (untreated) is not suitable anymore.<\/b> It is true that Wolbachia could theoretically spread from the deployment areas into the untreated control zones, however the rate of spread is known to be relatively slow especially in dengue urban environments like these (100-200m per year; Schmidt et al PLoS Biol 2017). Given the size of the control zone (117km2 in Rio de Janeiro, and 51km2 in Niteroi), it is highly unlikely that Wolbachia establishment will occur in any meaningful way beyond the border area of the control zones within the 5 year timeframe of this study.  \n3.    The authors stated that the reason for favoring quasi-experimental design (QED) over randomized controlled trial (RCT) was due to time constraints as stakeholders and funders wanted to scale-up the deployment of Wolbachia to accelerate the control of the emergent Zika virus in this region. However, in this set-up, to carefully randomize zones as treated or not should not take much time. In fact, since the incidence of Aedes-borne virus infections is similar between treated and untreated zones (Figure 2), that should be a motivation for randomizing the zones. I am thinking there are other reasons for ditching RCT. The authors should elaborate on this.<\/b> The randomization itself would not necessarily take a lot of time, although there would be additional work required to define an adequate number of spatial units for randomization (ideally based on a power calculation), and define those spatial units with \u2018hard\u2019 borders which minimise contamination between treated and untreated areas. The time delays come from the added complexity of conducting the intensive community and stakeholder engagement that is needed prior to releases, and conducting the deployments themselves, across a fragmented set of release areas interspersed with untreated control areas, compared to conducting these engagement and deployment activities in a contiguous release area. Please see our response to Reviewer 1\u2019s comments #1, #7 and #11 for further discussion of the reasons for non-randomisation, and for the references to where we have improved discussion of this point in the manuscript text. \n4.    For the controlled interrupted analysis, the authors plan to perform first, the descriptive analysis of the seasonal and inter-annual trends in the Aedes-borne infection notifications. It will be great if the authors are more specific about the types of descriptive analysis they intend to carry out. Also, a schematic of the expected trend in the notifications accounting for confounders will greatly help the protocol<\/b> The descriptive analysis will simply describe the seasonal and interannual trends, as stated. I.e. the calendar months in which dengue incidence has historically been highest and lowest in the two cities, and the range in annual case counts and per capita incidence. We don\u2019t see that this level of detail is of value to the reader here. We don\u2019t understand the reviewer\u2019s suggestion about a schematic of expected trend in notifications. We show in figure 2 the historical trends in dengue incidence in the intervention area and untreated control area for each city; the lines for intervention and control area can be expected to diverge if Wolbachia successfully interrupts dengue transmission. Minor comments \n5.    The title indicated controlling \u201carboviral disease incidence\u201d. The authors can be more specific if they change that to either \u201cAedes-borne disease incidence\u201d or something more specific.<\/b> We have changed the wording in the title to \u2018Aedes-borne disease\u2019 as suggested. \n6.    I think the clause in the fourth line [of the abstract] will flow better if \u201cAedes-borne diseases dengue, chikungunya and Zika\u201d is changed to  \u201cAedes-borne diseases (dengue, chikungunya and Zika).<\/b> We have kept the original wording here, because strictly these three are not the only Aedes¬-borne diseases, but they are the Aedes-borne diseases were are considering in this protocol. \n7.    Change \u201ckm2\u201d to \u201ckm2\u201d<\/b> This change has been made. \n8.    Figure 2 shows the comparative incidence of dengue for the treated and untreated regions. What about Zika and Chikungunya that the study is trying to control too? I think this is a dengue control study that has the potential to control Zika and Chikungunya in these regions. It will be great if the authors make it appear so. As it is, it seems to be a study deliberately targeting all the three Aedes-borne diseases<\/b> See response to comment #13, Reviewer 1. Historical chikungunya data for the intervention areas and control areas is now included as Figure 3.","URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2#referee-comment-5567","order":3,"name":"referee-comment-5567","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.27081.r74998, Stephen Waterman, Division of Vector-Borne Diseases\u00a0(DVBD), National Center for Emerging and Zoonotic Infectious Diseases (NCEZID), Centers for Disease Control and Prevention\u00a0(CDC), San Juan, Puerto Rico, 22 Dec 2020, version 2, indexed","URL":"https:\/\/f1000research.com\/articles\/8-1328\/v2#referee-response-74998","order":4,"name":"referee-response-74998","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This study is funded by the Bill and Melinda Gates Foundation (OPP1099252); the Brazilian Ministry of Health (DECIT; TED 09\/2016); and the US Centers for Disease Control (CDC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":5,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}