We audited the locations and point-of-sale marketing activities of RMDs in school neighborhoods and merged auditing data with school survey data on a large sample of adolescents in California. We paid particular attention to child-appealing marketing activities, which were presumably more influential to adolescents than general marketing activities. Instead of aggregating data at zip code or census tract level, we examined individual-level outcomes and simultaneously accounted for between- and within-school variations. Our first hypothesis that a closer proximity of RMDs is associated with a greater likelihood of adolescents’ marijuana use was not supported by the findings. In fact, a closer proximity was found to be associated with lower likelihoods of some outcomes in some model specifications in sensitivity analysis. Although no similar studies on RMDs can be used to compare to our findings, existing evidence on medical marijuana dispensaries did show mixed relationships between dispensaries’ proximity and marijuana use among adolescents. Whether and how the proximity of RMDs in school neighborhoods is associated with adolescents’ marijuana use outcomes deserve further research. Our second hypothesis that the presence of child-appealing marketing activities in RMDs is associated with a greater likelihood of adolescents’ marijuana use was not supported by the findings, either. However, when we examined the third hypothesis , we did find some evidence that child-appealing products, packages,vertical farming systems and paraphernalia in RMDs in very close proximity to schools might be associated with a greater odds of current use or heavy use.
It is likely that these items were resold or freely distributed to adolescents by third party adults, such as older friends, relatives, street dealers, who resided or worked in school neighborhoods. The interaction effects of RMDs’ proximity and marketing activities were not found on child-appealing advertisements. One plausible explanation is that nearly all RMDs we audited complied with age restrictions by ID check. Adolescents therefore had little chance to see advertisements inside of the RMDs, which could not be taken out by third party adults. It should be noted that the findings on interaction effects were sensitive to the selection of proximity cutoffs and model specifications. This is why we considered the strength of the evidence on interaction effects to be only moderate.The findings have policy implications. If the impacts of point-of-sale child-appealing marketing activities depend upon the proximity of RMDs to schools, stronger surveillance may be needed to monitor marijuana-related perceptions and behaviors in schools that have RMDs located near to them. Even though almost all states with legal sales of recreational marijuana prohibit products and advertisements specifically targeting children, our dispensary auditing data demonstrated a wide presence of these prohibited items in school neighborhoods. Actions should be taken to reduce child-appealing marketing activities and prevent adolescents from potential exposure. This study has limitations. First, the cross-sectional examination of associations should not be interpreted as causality. Second, the study sample was restricted to 73% of the CSTS 2017-8 schools that completed the survey on or after February 1st, 2018.
The generalizability of the findings to the entire California may be a concern. Third, we audited RMDs after the CSTS 2017-8 was completed in order to have an accurate and complete list of surveyed schools and conduct auditing in a cost-efficient manner. To what extent our observations on RMDs applied to the time when the schools were actually surveyed was unknown. Fourth, the marketing activity predictors were indicators of presence instead of continuous quantity measures due to feasibility considerations in fieldwork. We were not able to examine the quantity of marketing items . Lastly, our findings may not be applied to RMDs around adolescents’ homes, adolescents in private schools, or jurisdictions outside of California. With the dynamics in marijuana retail environments and government surveillance and law enforcement, the findings in the early stage of recreational marijuana commercialization may also lack generalizability to the most recent regulatory and retail contexts. In the past decade, the massive scale-up of insecticide treated bed nets and indoor residual spraying , together with the use of artemisinin-based combination treatments, have led to major changes in malaria epidemiology and vector biology. Overall malaria prevalence and incidence have been greatly reduced worldwide. But the reductions in malaria have not been achieved uniformly; some sites have experienced continued reductions in both clinical malaria and overall parasite prevalence, while other sites showed stability or resurgence in malaria despite high coverage of ITNs and IRS. Persistence and resurgence of vector populations continues to be an important issue for malaria control and elimination. More importantly, extensive use of ITNs and IRS has created intensive selection pressures for malaria vector insecticide resistance as well as for potential outdoor transmission, which appears to be limiting the success of ITNs and IRS. For example, in Africa, where malaria is most prevalent and pyrethroid-impregnated ITNs have been used for more than a decade, there is ample evidence of the emergence and spread of pyrethroid resistance in Anopheles gambiae s.s., the major African malaria vector, as well as in An. arabiensis and An. funestus s.l.. Both the prevalence of An. gambiae s.s. resistance to pyrethroids and DDT and the frequency of knock-down resistance have reached alarming levels throughout Africa from 2010–2012.
Unfortunately, pyrethroids are the only class of insecticides that the World Health Organization recommends for the treatment of ITNs . Furthermore, a number of recent studies have documented a shift in the biting behavior of An. gambiae s.s. and An. funestus, from biting exclusively indoors at night to biting both indoors and outdoors during early evening and morning hours when people are active but not protected by IRS or ITNs, or to biting indoors but resting outdoors. Apart from these intraspecific changes in biting behavior, shifts in vector species composition, i.e., from the previously predominant indoor-biting An. gambiae s.s. to the concurrently predominant species An. arabiensis, which prefers to bite and rest outdoors in some parts of Africa, can also increase outdoor transmission. Because IRS and ITNs have little impact on outdoor-resting and outdoor and early-biting vectors, outdoor transmission represents one of the most important challenges in malaria control. New interventions are urgently needed to augment current public health measures and reduce outdoor transmission. Larval control has historically been very successful and is widely used for mosquito control in many parts of the developed world, but is not commonly used in Africa. Field evaluation of anopheline mosquitoes in Africa found that larviciding was effective in killing anopheline larvae and reducing adult malaria vector abundance in various sites. Microbial larvicides are effective in controlling malaria vectors,cannabis grow room and they can be used on a large scale in combination with ongoing ITN and IRS programs. However, conventional larvicide formulations are associated with high material and operational costs due to the need for frequent habitat re-treatment, i.e., weekly re-treatment, as well as logistical issues in the field. Recently, an improved slow-release larvicide formulation was field-tested for controlling Anopheles mosquitoes, yielding an effective duration of approximately 4 weeks. Considering the monthly reapplication interval, this still may not be a cost-effective product for large-scale application. The new US EPA-approved long-lasting formulation, FourStar Microbial Briquets , is potentially effective for up to 6 months , and preliminary data suggest that it is effective in malaria mosquito control [GZ, unpublished data]. Field-testing is needed to determine the efficacy and cost-effectiveness of this long-lasting larvicide. The central objective of this study is to determine the effectiveness and cost-effectiveness of long-lasting microbial larviciding on the incidence of clinical malaria and the reduction of transmission intensity. The hypothesis is that adding LLML to ongoing ITN and IRS programs will lead to significant reductions in both indoor and outdoor malaria transmission and malaria incidence as well as cost savings. This paper describes a protocol for evaluating the impact of LLML in reducing malaria vector populations and clinical malaria incidence.For purposes of planning and conducting an evaluation of the intervention, we will subdivide the field area into villages , which is the smallest administrative unit in Kenya. Using villages as clusters has advantages over random sampling. First, the clinical records in health centers or hospitals in Kenya generally include the name of the village and sublocation ; therefore, clinical malaria cases can be traced back to the village level. Second, villages have been conveniently used as intervention/ control clusters in previous trials.
Our field team will conduct the demographic surveys before the start of the intervention. Each team will be provided with a printed overview map and a handheld Google Nexus 7 tablet. A surveillance team, comprising a field technician, a reporter, and a local guide, will visit every compound to explain the study procedures, tally inhabitants, and collect information on house characteristics. If the head of the compound agrees to participate, we will record the geographical coordinates of the main house of the compound and compound codes will be written in permanent marker on the front wall next to the door. We will record the genders and ages of all compound members on questionnaire forms using the on-site Google Nexus 7, which will update the database in real time together with the GPS coordinates of the surveyed compound. We will map the locations of all compounds using ArcGIS 10 . Demographic surveillance will be done in year 1, 6–12 months prior to intervention . We will draw village boundaries based on the demographic surveys and confirm it with the field teams and the database manager. If a village is too small , we will combine the village with a neighboring village to form one cluster. Total and age- and gender-specific populations will be aggregated at the cluster level.Clinical malaria records will be collected from 8 to 12 months prior to intervention, to calculate baseline incidence rate at each cluster for cluster randomization, through to 8 to 12 months after all interventions . We will collect information on clinical malaria cases retrospectively from all government-run hospitals, health care centers, and clinics located either within the study area itself or within catchment areas overlapping the study area. We will obtain clinical data from the treatment centers through the malaria control office of Kakamega and Vihiga counties, Kenya. We will also collect patient- and treatment-related information, including age, gender, date of diagnosis, parasite species, village of patient , and prescriptions given. All personal identifiers will be excluded from this study. A clinical malaria case is defined as an individual with fever and other related symptoms such as chills, severe malaise, headache, or vomiting in the presence of a Plasmodium-positive blood smear. The clinical malaria incidence rate is calculated as the number of clinical malaria episodes divided by the total person time at risk based on demographic surveys. We will also collect the aggregated monthly diarrhea data at each site along with clinical malaria records from local health clinics and hospitals. We will not conduct prospective passive surveillance, active home visits, or cross-sectional blood surveys. We will calculate the clinical malaria incidence rate separately for each cluster, different study period and different age group . We will include all clinical malaria cases in our study, including cases diagnosed during the four study periods : preintervention period: baseline clinical malaria records started at least 8–12 months prior to the application of long-lasting microbial larvicides till intervention, intervention period: all clinical records during the intervention period, the 8-month wash-out period, and post intervention period: clinical malaria records till 8–12 months after the last round of larvicide application.Permission to use microbial larvicides for malaria vector control has been obtained from the Pest Control Products Board of Kenya. Ethical clearance has been approved by the Scientific and Ethical Unit of the Kenya Medical Research Institute . As described, aggregated clinical data will be obtained from the treatment centers through the malaria control offices of Kakamega and Vihiga counties, Kenya. According to US Department of Health and Human Services Code of Federal Regulations 45 CFR 46.101 part 4 , these data are in the category of exempt human subjects research, which involves the study of existing data, documents, or records, with no collection of subject-level information. Informed consent will be obtained from each participant. All investigative team members in the United States, Kenya, and Australia have no financial conflict of interest with the larvicide manufacturer, Central Life Sciences.We will conduct baseline malaria vector surveillance at least 4 months prior to any application of LLMLs .