A method for estimating colony size using queen fecundity in termites under field conditions

Colony size in social insects is one of the most important factors in shaping their self-organized system. It affects a wide variety of traits such as foraging and defense strategies, social immune responses, the degree of polymorphism, and reproductive output. However, colony size estimation of subterranean termites in the field has been challenging, due to their extremely cryptic biology and multiple site-nesting behavior. Since natural selection favors workers that maximize the number of their siblings, the amount of egg production may reflect the number of workers in the colony. Here, we report a method for inferring colony size in the field using total egg production in each colony from a subterranean termite, Reticulitermes speratus. Our investigation of field colonies revealed that the body weight of queens reaches a peak and had the largest variance in June and July and accurately predicts the number of eggs laid by the queen per 24 h. Using laboratory-reared colonies, we found that the total egg production in each colony is proportional to the number of workers. We also estimated the colony size of 198 field colonies and found that the median and maximum colony size was 24,500 and 451,800 workers per colony. The method for inferring colony size presented here may also be applicable to termite species with a clear seasonality in egg production. The colony size estimate will contribute to understanding the life history strategies and social systems of termites.

Population estimation and harm reduction among people who inject drugs in Addis Ababa, Ethiopia

Background

Injecting drug use is known to contribute significantly to the spread of the HIV epidemic in many parts of the developing world. Due to the hidden nature and stigma of the problem, it is difficult to study using routine surveys. Therefore, this study aims to estimate the number of people who inject drugs in Addis Ababa, Ethiopia, and to describe the epidemiological and social situation related to HIV among people who inject drugs.

Methods

The study used rapid assessment methods, followed by combined methods of estimating populations, using nomination and multiplier methods. The combined methods used two datasets: the first includes the proportion of people who use services within a year as a multiplier, and the second, a count of the list of people with a problem who used the specific service within a year as a benchmark. The rapid assessment incorporated different qualitative tools to elicit information related to injectable drugs, using existing data sources, in-depth interviews, and focus group discussions.

Results

The study estimated a total of 4068; with 95% CI (3196, 5207) people who inject drugs (PWIDs) in Addis Ababa. The study found people who inject drugs were young in age, male, with a lower educational status, unmarried, and living in small clerical business. People who inject drugs and participated in the study were more likely to use additional substances like alcohol, khat, and cannabis. The most common form of injectable drug used was heroin, and most of the people who inject drugs reported sharing syringes and needles. A high proportion of study subjects also disclosed having positive test results for HIV, hepatitis B, and C.

Conclusion

The population size of people who inject drugs in Addis Ababa is high. Lack of service in harm reduction in the city has made PWIDs vulnerable and at higher risk for HIV/AIDs and hepatitis B and C. Therefore, responsible bodies must start implementing the essential harm reduction strategies given by the World Health Organization.

Reporting of core items in hierarchical Bayesian analysis for aggregating N-of-1 trials to estimate population treatment effects is suboptimal

OBJECTIVES

N-of-1 trials can be aggregated to estimate population treatment effects using hierarchical Bayesian models. It is very important to report core items in hierarchical Bayesian analysis. In this study, we assessed reporting of items in hierarchical Bayesian analysis for aggregating N-of-1 trials to estimate population treatment effects.

STUDY DESIGN AND SETTING

This was a systematic literature review of aggregating N-of-1 trials by hierarchical Bayesian models to estimate population treatment effects. A comprehensive search was performed to collect eligible articles. Pilot studies, formal N-of-1 trials and reports in which the data were reanalyzed using hierarchical Bayesian methods, were included. The information of reported items related with hierarchical Bayesian analysis was extracted by two independent reviewers. The guideline "ROBUST," developed for reporting Bayesian analysis of clinical studies, was published in Journal of Clinical Epidemiology in 2005. We assessed the included reports using ROBUST criteria and 18 other important items.

RESULTS

After careful screening, 11 studies were identified to be eligible for inclusion. There were three pilot studies, four formal trials, and four reports in which the data were reanalyzed using hierarchical Bayesian methods. The number of reported items in ROBUST criteria ranged from six to seven, with a median number of six. Five of eleven included articles reported all items of the ROBUST criteria. But for justification and sensitivity analysis in prior distribution items, other items were reported in all of the included articles. Software and analysis data set items were reported the most frequently in additional items excluded from the ROBUST criteria. Less than half of the studies reported the other additional items.

CONCLUSION

Reporting of core items in hierarchical Bayesian analysis for aggregating N-of-1 trials to estimate population treatment effects is suboptimal. A PRISMA-like guidance on reviews of Bayesian N-of-1 trials may be required in the future.