A continuous-time formulation for spatial capture-recapture models

Spatial capture-recapture (SCR) models are relatively new but have become the standard approach used to estimate animal density from capture-recapture data. It has in the past been impractical to obtain sufficient data for analysis on species that are very difficult to capture such as elusive carnivores that occur at low density and range very widely. Advances in technology have led to alternative ways to virtually "capture" individuals without having to physically hold them. Some examples of these new non-invasive sampling methods include scat or hair collection for genetic analysis, acoustic detection and camera trapping. In traditional capture-recapture (CR) and SCR studies populations are sampled at discrete points in time leading to clear and well defined occasions whereas the new detector types mentioned above sample populations continuously in time. Re- searchers with data collected continuously currently need to define an appropriate occasion and aggregate their data accordingly thereby imposing an artificial construct on their data for analytical convenience. This research develops a continuous-time (CT) framework for SCR models by treating detections as a temporal non homogeneous Poisson process (NHPP) and replacing the usual SCR detection function with a continuous detection hazard func- tion. The general CT likelihood is first developed for data from passive (also called "proximity") detectors like camera traps that do not physically hold individuals. The likelihood is then modified to produce a likelihood for single-catch traps (traps that are taken out of action by capturing an animal) that has proven difficult to develop with a discrete-occasion approach. The lack of a suitable single-catch trap likelihood has led to researchers using a discrete-time (DT) multi-catch trap estimator to analyse single-catch trap data. Previous work has found the DT multi-catch estimator to be robust despite the fact that it is known to be based on the wrong model for single-catch traps (it assumes that the traps continue operating after catching an individual). Simulation studies in this work confirm that the multi-catch estimator is robust for estimating density when density is constant or does not vary much in space. However, there are scenarios with non-constant density surfaces when the multi-catch estimator is not able to correctly identify regions of high density. Furthermore, the multi-catch estimator is known to be negatively biased for the intercept parameter of SCR detection functions and there may be interest in the detection function in its own right. On the other hand the CT single-catch estimator is unbiased or nearly so for all parameters of interest including those in the detection function and those in the model for density. When one assumes that the detection hazard is constant through time there is no impact of ignoring capture times and using only the detection frequencies. This is of course a special case and in reality detection hazards will tend to vary in time. However when one assumes that the effects of time and distance in the time-varying hazard are independent, then similarly there is no information in the capture times about density and detection function parameters. The work here uses a detection hazard that assumes independence between time and distance. Different forms for the detection hazard are explored with the most exible choice being that of a cyclic regression spline. Extensive simulation studies suggest as expected that a DT proximity estimator is unbiased for the estimation of density even when the detection hazard varies though time. However there are indirect benefits of incorporating capture times because doing so will lead to a better fitting detection component of the model, and this can prevent unexplained variation being erroneously attributed to the wrong covariate. The analysis of two real datasets supports this assertion because the models with the best fitting detection hazard have different effects to the other models. In addition, modelling the detection process in continuous-time leads to a more parsimonious approach compared to using DT models when the detection hazard varies in time. The underlying process is occurring in continuous-time and so using CT models allows inferences to be drawn about the underlying process, for example the time- varying detection hazard can be viewed as a proxy for animal activity. The CT formulation is able to model the underlying detection hazard accurately and provides a formal modelling framework to explore different hypotheses about activity patterns. There is scope to integrate the CT models developed here with models for space usage and landscape connectivity to explore these processes on a finer temporal scale. SCR models are experiencing a rapid growth in both application and method development. The data generating process occurs in CT and hence a CT modelling approach is a natural fit and opens up several opportunities that are not possible with a DT formulation. The work here makes a contribution by developing and exploring the utility of such a CT SCR formulation

A continuous-time formulation for spatial capture-recapture models

Spatial capture-recapture (SCR) models are relatively new but have become the standard approach used to estimate animal density from capture-recapture data. It has in the past been impractical to obtain sufficient data for analysis on species that are very difficult to capture such as elusive carnivores that occur at low density and range very widely. Advances in technology have led to alternative ways to virtually “capture" individuals without having to physically hold them. Some examples of these new non-invasive sampling methods include scat or hair collection for genetic analysis, acoustic detection and camera trapping. In traditional capture-recapture (CR) and SCR studies populations are sampled at discrete points in time leading to clear and well defined occasions whereas the new detector types mentioned above sample populations continuously in time. Researchers with data collected continuously currently need to define an appropriate occasion and aggregate their data accordingly thereby imposing an artificial construct on their data for analytical convenience. This research develops a continuous-time (CT) framework for SCR models by treating detections as a temporal non homogeneous Poisson process (NHPP) and replacing the usual SCR detection function with a continuous detection hazard function. The general CT likelihood is first developed for data from passive (also called “proximity") detectors like camera traps that do not physically hold individuals. The likelihood is then modified to produce a likelihood for single-catch traps (traps that are taken out of action by capturing an animal) that has proven difficult to develop with a discrete-occasion approach. The lack of a suitable single-catch trap likelihood has led to researchers using a discrete-time (DT) multi-catch trap estimator to analyse single-catch trap data. Previous work has found the DT multi-catch estimator to be robust despite the fact that it is known to be based on the wrong model for single-catch traps (it assumes that the traps continue operating after catching an individual). Simulation studies in this work confirm that the multi-catch estimator is robust for estimating density when density is constant or does not vary much in space. However, there are scenarios with non-constant density surfaces when the multi-catch estimator is not able to correctly identify regions of high density. Furthermore, the multi-catch estimator is known to be negatively biased for the intercept parameter of SCR detection functions and there may be interest in the detection function in its own right. On the other hand the CT single-catch estimator is unbiased or nearly so for all parameters of interest including those in the detection function and those in the model for density. When one assumes that the detection hazard is constant through time there is no impact of ignoring capture times and using only the detection frequencies. This is of course a special case and in reality detection hazards will tend to vary in time. However when one assumes that the effects of time and distance in the time-varying hazard are independent, then similarly there is no information in the capture times about density and detection function parameters. The work here uses a detection hazard that assumes independence between time and distance. Different forms for the detection hazard are explored with the most flexible choice being that of a cyclic regression spline. Extensive simulation studies suggest as expected that a DT proximity estimator is unbiased for the estimation of density even when the detection hazard varies though time. However there are indirect benefits of incorporating capture times because doing so will lead to a better fitting detection component of the model, and this can prevent unexplained variation being erroneously attributed to the wrong covariate. The analysis of two real datasets supports this assertion because the models with the best fitting detection hazard have different effects to the other models. In addition, modelling the detection process in continuous-time leads to a more parsimonious approach compared to using DT models when the detection hazard varies in time. The underlying process is occurring in continuous-time and so using CT models allows inferences to be drawn about the underlying process, for example the timevarying detection hazard can be viewed as a proxy for animal activity. The CT formulation is able to model the underlying detection hazard accurately and provides a formal modelling framework to explore different hypotheses about activity patterns. There is scope to integrate the CT models developed here with models for space usage and landscape connectivity to explore these processes on a finer temporal scale. SCR models are experiencing a rapid growth in both application and method development. The data generating process occurs in CT and hence a CT modelling approach is a natural fit and opens up several opportunities that are not possible with a DT formulation. The work here makes a contribution by developing and exploring the utility of such a CT SCR formulation

South African quantity surveyors: issues of gender and race in the workplace

A web-based questionnaire survey of the opinions of SA quantity surveyors was undertaken to establish gender- and race-based differences in job satisfaction. Issues explored included demographic factors, issues of gender and race in the workplace, and gender and racial harassment and discrimination at work. ‘Significant’ differences on the basis of gender exist on a number of issues. Women, more than men, have strong positive feelings regarding their levels of job satisfaction, feel that their career expectations have been fulfilled, would choose the same career again, and would unequivocally recommend the career to others. Females see QS practices as male-dominated, see themselves as being blocked from advancement to managerial ranks, participating less in decision-making, and remunerated at a lower level than equivalent colleagues. Issues important to women include: gender representivity in the profession, flexible working hours and maternity leave above the statutory minimum. Although both gender groups report racial harassment and discrimination at work, women experience significantly more sexual and gender harassment and religious and gender discrimination than do males. ‘Significant’ differences on the basis of race are evident concerning: feelings of job satisfaction and views on maternity / paternity leave above statutory minima. ‘Highly significant’ differences on the basis of race arise over issues of: being subjected to greater supervision because of race, not being allowed to contribute meaningfully to the decision-making process, viewing PDI status as a valid basis for promotion, seeing race representivity in the profession as important in combating discrimination at work, having personally experienced racial harassment and discrimination at work, and seeing respect for individual diversity in the workplace as important - with ‘Whites’ viewing these issues less ‘empathically’ than their ‘Non-white’ counterparts. The results provide valuable indicators for how the quantity surveying firms can create a more conducive work environment for professional staff, particularly females.&nbsp

South African quantity surveyors: issues of gender and race in the workplace

A web-based questionnaire survey of the opinions of SA quantity surveyors was undertaken to establish gender- and race-based differences in job satisfaction. Issues explored included demographic factors, issues of gender and race in the workplace, and gender and racial harassment and discrimination at work. 'Significant' differences on the basis of gender exist on a number of issues. Women, more than men, have strong positive feelings regarding their levels of job satisfaction, feel that their career expectations have been fulfilled, would choose the same career again, and would unequivocally recommend the career to others. Females see QS practices as male-dominated, see themselves as being blocked from advancement to managerial ranks, participating less in decision-making, and remunerated at a lower level than equivalent colleagues. Issues important to women include : gender representivity in the profession, flexible working hours and maternity leave above the statutory minimum. Although both gender groups report racial harassment and discrimination at work, women experience significantly more sexual and gender harassment and religious and gender discrimination than do males. 'Significant' differences on the basis of race are evident concerning : feelings of job satisfaction and views on maternity / paternity leave above statutory minima. 'Highly significant' differences on the basis of race arise over issues of : being subjected to greater supervision because of race, not being allowed to contribute meaningfully to the decision-making process, viewing PDI status as a valid basis for promotion, seeing race representivity in the profession as important in combating discrimination at work, having personally experienced racial harassment and discrimination at work, and seeing respect for individual diversity in the workplace as important - with 'Whites' viewing these issues less 'empathically' than their 'Non-white' counterparts. The results provide valuable indicators for how the quantity surveying firms can create a more conducive work environment for professional staff, particularly females

Using continuous-time spatial capture–recapture models to make inference about animal activity patterns

This work was part‐funded by EPSRC Grant EP/I000917/1, by the research fellowship RF‐2018‐213/9, and the fieldwork was funded by the Summerlee Foundation and Panthera.1. Quantifying the distribution of daily activity is an important component of behavioral ecology. Historically, it has been difficult to obtain data on activity patterns, especially for elusive species. However, the development of affordable camera traps and their widespread usage has led to an explosion of available data from which activity patterns can be estimated. 2. Continuous-time spatial capture?recapture (CT SCR) models drop the occasion structure seen in traditional spatial and nonspatial capture?recapture (CR) models and use the actual times of capture. In addition to estimating density, CT SCR models estimate expected encounters through time. Cyclic splines can be used to allow flexible shapes for modeling cyclic activity patterns, and the fact that SCR models also incorporate distance means that space-time interactions can be explored. This method is applied to a jaguar dataset. 3. Jaguars in Belize are most active and range furthest in the evening and early morning and when they are located closer to the network of trails. There is some evidence that females have a less variable pattern than males. The comparison between sexes demonstrates how CT SCR can be used to explore hypotheses about animal behavior within a formal modeling framework. 4. SCR models were developed primarily to estimate and model density, but the models can be used to explore processes that interact across space and time, especially when using the CT SCR framework that models the temporal dimension at a finer resolution.Publisher PDFPeer reviewe

Substance abuse and HIV risk behaviours amongst primary health care service users in Cape Town

Objective: To document prevalence of, and association between, substance use and HIV risk behaviours among primary care patients.Method: Cross-sectional survey. Four primary care clinics in Cape Town. We selected clinics using stratified sampling, and systematically selected 131 patients from attendance logs. We assessed substance use with the Alcohol, Smoking and Substance Involvement Screening Test, and HIV risk with items addressing injection drug use, blood-sharing rituals, and sexual risk behaviours. Results: Substances most used at hazardous levels were tobacco (28.2%) and alcohol (14.8%). Among possible HIV risk factors, highest prevalence was participation in blood-sharing rituals (25%), and having had an STI (19.8%). An association between substance use and sexual risk behaviours was only found among those aged 18-24. Conclusion: In younger patients, presence of substance use or HIV risk behaviours increases the probability that the other is present. Keywords: substance abuse, HIV risk behaviours, primary care South African Psychiatry Review Vol. 8(4) 2005: 160-16

Substance abuse and HIV risk behaviours amongst primary health care service users in Cape Town

Objective: To document prevalence of, and association between, substance use and HIV risk behaviours among primary care patients.Method: Cross-sectional survey. Four primary care clinics in Cape Town. We selected clinics using stratified sampling, and systematically selected 131 patients from attendance logs. We assessed substance use with the Alcohol, Smoking and Substance Involvement Screening Test, and HIV risk with items addressing injection drug use, blood-sharing rituals, and sexual risk behaviours. Results: Substances most used at hazardous levels were tobacco (28.2%) and alcohol (14.8%). Among possible HIV risk factors, highest prevalence was participation in blood-sharing rituals (25%), and having had an STI (19.8%). An association between substance use and sexual risk behaviours was only found among those aged 18-24. Conclusion: In younger patients, presence of substance use or HIV risk behaviours increases the probability that the other is present

Nonlinear mixed effects modeling of gametocyte carriage in patients with uncomplicated malaria

<p>Abstract</p> <p>Background</p> <p>Gametocytes are the sexual form of the malaria parasite and the main agents of transmission. While there are several factors that influence host infectivity, the density of gametocytes appears to be the best single measure that is related to the human host's infectivity to mosquitoes. Despite the obviously important role that gametocytes play in the transmission of malaria and spread of anti-malarial resistance, it is common to estimate gametocyte carriage indirectly based on asexual parasite measurements. The objective of this research was to directly model observed gametocyte densities over time, during the primary infection.</p> <p>Methods</p> <p>Of 447 patients enrolled in sulphadoxine-pyrimethamine therapeutic efficacy studies in South Africa and Mozambique, a subset of 103 patients who had no gametocytes pre-treatment and who had at least three non-zero gametocyte densities over the 42-day follow up period were included in this analysis.</p> <p>Results</p> <p>A variety of different functions were examined. A modified version of the critical exponential function was selected for the final model given its robustness across different datasets and its flexibility in assuming a variety of different shapes. Age, site, initial asexual parasite density (logged to the base 10), and an empirical patient category were the co-variates that were found to improve the model.</p> <p>Conclusions</p> <p>A population nonlinear modeling approach seems promising and produced a flexible function whose estimates were stable across various different datasets. Surprisingly, dihydrofolate reductase and dihydropteroate synthetase mutation prevalence did not enter the model. This is probably related to a lack of power (quintuple mutations n = 12), and informative censoring; treatment failures were withdrawn from the study and given rescue treatment, usually prior to completion of follow up.</p

Drowning in data, thirsty for information and starved for understanding: A biodiversity information hub for cooperative environmental monitoring in South Africa

The world is firmly cemented in a notitian age (Latin: notitia, meaning data) – drowning in data, yet thirsty for information and the synthesis of knowledge into understanding. As concerns over biodiversity declines escalate, the volume, diversity and speed at which new environmental and ecological data are generated has increased exponentially. Data availability primes the research and discovery engine driving biodiversity conservation. South Africa (SA) is poised to become a world leader in biodiversity conservation. However, continent-wide resource limitations hamper the establishment of inclusive technologies and robust platforms and tools for biodiversity informatics. In this perspectives piece, we bring together the opinions of 37 co-authors from 20 different departments, across 10 SA universities, 7 national and provincial conservation research agencies, and various institutes and private conservation, research and management bodies, to develop a way forward for biodiversity informatics in SA. We propose the development of a SA Biodiversity Informatics Hub and describe the essential components necessary for its design, implementation and sustainability. We emphasise the importance of developing a culture of cooperation, collaboration and interoperability among custodians of biodiversity data to establish operational workflows for data synthesis. However, our biggest challenges are misgivings around data sharing and multidisciplinary collaboration

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to &lt;90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], &gt;300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of &lt;15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P&lt;0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P&lt;0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years