Detection of Outliers in Time Series Data

This thesis presents the detection of time series outliers. The data set used in this work is provided by the GasDay Project at Marquette University, which produces mathematical models to predict the consumption of natural gas for Local Distribution Companies (LDCs). Flow with no outliers is required to develop and train accurate models. GasDay is using statistical approaches motivated by normally distributed samples such as the 3 -sigma rule and the 5 -sigma rule to aid the experts in detecting outliers in residuals from the models. However, the Jarque-Bera statistical test shows that the residuals from the GasDay models are not normally distributed. We present an explanation of Density Based Spatial Clustering of Applications with Noise (DBSCAN) and how it is used to detect time series outliers. We have introduced a new application for the DBSCAN algorithm by adapting it to detect outliers in natural gas flow. The performance of DBSCAN is compared with GasDay\u27s existing technique. Five data sets from temperature-sensitive operating areas with identified outliers and 1000 data sets with synthetic outliers are used in the evaluation process. The 1000 synthetic data sets are prepared using the same empirical distribution as one of the identified data set. This work indicates that DBSCAN has shown some improvement in detecting outliers over GasDays existing technique and merits further exploration

Bioinformatics Systems And Mathematical Models For Improved Understanding Of Malaria Transmission, Control, And Elimination

The leading malaria vector control strategies (i.e., long-lasting insecticidal nets and indoor residual spraying) can reduce indoor transmission, but these tools alone are insufficient to eliminate it. Strategies that target adult mosquitoes when they feed on humans or animals outdoors or target mosquito immature stages are also needed to achieve malaria elimination. Improved data systems for integrating diverse experimental observations and research groups, as well as process-explicit mathematical models for evaluating them are both essential to achieving these goals. We have developed a generic schema and data repositories for the studies of malaria vectors that encompass a wide variety of different experimental designs that rapidly generate large data volumes. We extended a malaria transmission model to examine the relationship between transmission, control, and the proportion of blood meals a vector population obtains from humans: Assuming the lower limit for this indicator of human feeding preference enabled derivation of simplified models for zoophagic vectors. We present differential equation models to describe the biological processes that mediate novel strategies to control malaria vectors by autodissemination of pyripoxyfen (PPF) as it is transferred from treated stations to the gravid mosquitoes and then to the aquatic habitats where it inhibits mosquito emergence. Data from most of the mosquito studies we reviewed conformed to our generic schema with four tables recording the experimental design, sorting of collections, details of samples, and additional observations. Our corresponding online repository includes 20 experiments, 8 projects, and 15 users at two institutes, resulting in 10 peer-reviewed publications. For zoophagic vectors, the results from model can be used to forecast the likely immediate and delayed impacts of an intervention using only three field-measurable parameters. For the autodissemination of PPF, sensitivity analysis indicates success of the strategy is plausible because the ≥ 80% coverage of aquatic habitats with PPF appears achievable with modest, biologically plausible values of field-measurable input parameters. Therefore, we have applied two of the computational sciences aspects (i.e., research data preparation using computer systems and scenario analysis with mathematical models) to address obstacles to the control and elimination of malaria

Biologically meaningful coverage indicators for eliminating malaria transmission.

Mosquitoes, which evade contact with long-lasting insecticidal nets and indoor residual sprays, by feeding outdoors or upon animals, are primary malaria vectors in many tropical countries. They can also dominate residual transmission where high coverage of these front-line vector control measures is achieved. Complementary strategies, which extend insecticide coverage beyond houses and humans, are required to eliminate malaria transmission in most settings. The overwhelming diversity of the world's malaria transmission systems and optimal strategies for controlling them can be simply conceptualized and mapped across two-dimensional scenario space defined by the proportion of blood meals that vectors obtain from humans and the proportion of human exposure to them which occurs indoors

Age grading \u3cem\u3eAn. gambiae\u3c/em\u3e and \u3cem\u3eAn. arabiensis\u3c/em\u3e using near infrared spectra and artificial neural networks

Background Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into \u3c or ≥ 7 days old with an average accuracy of 80%, achieved by training a regression model using partial least squares (PLS) and interpreted as a binary classifier. Methods and findings We explore whether using an artificial neural network (ANN) analysis instead of PLS regression improves the current accuracy of NIRS models for age-grading malaria transmitting mosquitoes. We also explore if directly training a binary classifier instead of training a regression model and interpreting it as a binary classifier improves the accuracy. A total of 786 and 870 NIR spectra collected from laboratory reared An. gambiae and An. arabiensis, respectively, were used and pre-processed according to previously published protocols. The ANN regression model scored root mean squared error (RMSE) of 1.6 ± 0.2 for An. gambiae and 2.8 ± 0.2 for An. arabiensis; whereas the PLS regression model scored RMSE of 3.7 ± 0.2 for An. gambiae, and 4.5 ± 0.1 for An. arabiensis. When we interpreted regression models as binary classifiers, the accuracy of the ANN regression model was 93.7 ± 1.0% for An. gambiae, and 90.2 ± 1.7% for An. arabiensis; while PLS regression model scored the accuracy of 83.9 ± 2.3% for An. gambiae, and 80.3 ± 2.1% for An. arabiensis. We also find that a directly trained binary classifier yields higher age estimation accuracy than a regression model interpreted as a binary classifier. A directly trained ANN binary classifier scored an accuracy of 99.4 ± 1.0 for An. gambiae and 99.0 ± 0.6% for An. arabiensis; while a directly trained PLS binary classifier scored 93.6 ± 1.2% for An. gambiae and 88.7 ± 1.1% for An. arabiensis. We further tested the reproducibility of these results on different independent mosquito datasets. ANNs scored higher estimation accuracies than when the same age models are trained using PLS. Regardless of the model architecture, directly trained binary classifiers scored higher accuracies on classifying age of mosquitoes than regression models translated as binary classifiers. Conclusion We recommend training models to estimate age of An. arabiensis and An. gambiae using ANN model architectures (especially for datasets with at least 70 mosquitoes per age group) and direct training of binary classifier instead of training a regression model and interpreting it as a binary classifier

Key traveller groups of relevance to spatial malaria transmission: a survey of movement patterns in four sub-Saharan African countries

Background: As malaria prevalence declines in many parts of the world due to widescale control efforts and as drug-resistant parasites begin to emerge, a quantitative understanding of human movement is becoming increasingly relevant to malaria control. However, despite its importance, significant knowledge gaps remain regarding human movement, particularly in sub-Saharan Africa. Methods: A quantitative survey of human movement patterns was conducted in four countries in sub-Saharan Africa: Mali, Burkina Faso, Zambia, and Tanzania, with three to five survey locations chosen in each country. Questions were included on demographic and trip details, malaria risk behaviour, children accompanying travellers, and mobile phone usage to enable phone signal data to be better correlated with movement. A total of 4352 individuals were interviewed and 6411 trips recorded. Results: A cluster analysis of trips highlighted two distinct traveller groups of relevance to malaria transmission: women travelling with children (in all four countries) and youth workers (in Mali). Women travelling with children were more likely to travel to areas of relatively high malaria prevalence in Mali (OR = 4.46, 95 % CI = 3.42–5.83), Burkina Faso (OR = 1.58, 95 % CI = 1.23–1.58), Zambia (OR = 1.50, 95 % CI = 1.20–1.89), and Tanzania (OR = 2.28, 95 % CI = 1.71–3.05) compared to other travellers. They were also more likely to own bed nets in Burkina Faso (OR = 1.77, 95 % CI = 1.25–2.53) and Zambia (OR = 1.74, 95 % CI = 1.34 2.27), and less likely to own a mobile phone in Mali (OR = 0.50, 95 % CI = 0.39–0.65), Burkina Faso (OR = 0.39, 95 % CI = 0.30–0.52), and Zambia (OR = 0.60, 95 % CI = 0.47–0.76). Malian youth workers were more likely to travel to areas of relatively high malaria prevalence (OR = 23, 95 % CI = 17–31) and for longer durations (mean of 70 days cf 21 days, p < 0.001) compared to other travellers. Conclusions: Women travelling with children were a remarkably consistent traveller group across all four countries surveyed. They are expected to contribute greatly towards spatial malaria transmission because the children they travel with tend to have high parasite prevalence. Youth workers were a significant traveller group in Mali and are expected to contribute greatly to spatial malaria transmission because their movements correlate with seasonal rains and hence peak mosquito densities. Interventions aimed at interrupting spatial transmission of parasites should consider these traveller groups

A New Test of a Theory about Old Mosquitoes

In vector control, it is widely accepted that killing adult mosquitoes would sharply reduce the proportion of old mosquitoes and cause the greatest changes to malaria transmission. The principle is based on a mathematical model of the sporozoite rate (the proportion of infective mosquitoes) that emphasized changes in mosquito age. Killing adult mosquitoes also reduces mosquito population densities, which are directly proportional to human biting rates (the number of bites, per person, per day). Eect sizes of vector control can be compared using sporozoite rates and human biting rates, which are commonly measured. We argue that human biting rates convey more use- ful information for planning, monitoring and evaluating vector control, and operational research should focus on understanding mosquito ecology

Effective autodissemination of pyriproxyfen to breeding sites by the exophilic malaria vector Anopheles arabiensis in semi-field settings in Tanzania

BACKGROUND Malaria vector control strategies that target adult female mosquitoes are challenged by the emergence of insecticide resistance and behavioural resilience. Conventional larviciding is restricted by high operational costs and inadequate knowledge of mosquito-breeding habitats in rural settings that might be overcome by the juvenile hormone analogue, Pyriproxyfen (PPF). This study assessed the potential for Anopheles arabiensis to pick up and transfer lethal doses of PPF from contamination sites to their breeding habitats (i.e. autodissemination of PPF). METHODS A semi-field system (SFS) with four identical separate chambers was used to evaluate PPF-treated clay pots for delivering PPF to resting adult female mosquitoes for subsequent autodissemination to artificial breeding habitats within the chambers. In each chamber, a tethered cow provided blood meals to laboratory-reared, unfed female An. arabiensis released in the SFS. In PPF-treated chambers, clay pot linings were dusted with 0.2 - 0.3 g AI PPF per pot. Pupae were removed from the artificial habitats daily, and emergence rates calculated. Impact of PPF on emergence was determined by comparing treatment with an appropriate control group. RESULTS Mean (95%CI) adult emergence rates were (0.21 +/- 0.299) and (0.95 +/- 0.39) from PPF-treated and controls respectively (p < 0.0001). Laboratory bioassay of water samples from artificial habitats in these experiments resulted in significantly lower emergence rates in treated chambers (0.16 +/- 0.23) compared to controls 0.97 +/- 0.05) (p < 0.0001). In experiments where no mosquitoes introduced, there were no significant differences between control and treatment, indicating that transfer of PPF to breeding sites only occurred when mosquitoes were present; i.e. that autodissemination had occurred. Treatment of a single clay pot reduced adult emergence in six habitats to (0.34 +/- 0.13) compared to (0.98 +/- 0.02) in the controls (p < 0.0001), showing a high level of habitats coverage amplification of the autodissemination event. CONCLUSION The study provides proof of principle for the autodissemination of PPF to breeding habitats by malaria vectors. These findings highlight the potential for this technique for outdoor control of malaria vectors and call for the testing of this technique in field trials

Why lockdown? Why national unity? Why global solidarity? Simplified arithmetic tools for decision-makers, health professionals, journalists and the general public to explore containment options for the 2019 novel coronavirus

As every country in the world struggles with the ongoing COVID-19 pandemic, it is essential that as many people as possible understand the epidemic containment, elimination and exclusion strategies required to tackle it. Simplified arithmetic models of COVID-19 transmission, control and elimination are presented in user-friendly Shiny and Excel formats that allow non-specialists to explore, query, critique and understand the containment decisions facing their country and the world at large. Although the predictive model is broadly applicable, the simulations presented are based on parameter values representative of the United Republic of Tanzania, which is still early enough in its epidemic cycle and response to avert a national catastrophe. The predictions of these models illustrate (1) why ambitious lock-down interventions to crush the curve represent the only realistic way for individual countries to contain their national-level epidemics before they turn into outright catastrophes, (2) why these need to be implemented so early, so stringently and for such extended periods, (3) why high prevalence of other pathogens causing similar symptoms to mild COVID-19 precludes the use of contact tracing as a substitute for lock down interventions to contain and eliminate epidemics, (4) why partial containment strategies intended to merely flatten the curve, by maintaining epidemics at manageably low levels, are grossly unrealistic, and (5) why local elimination may only be sustained after lock down ends if imported cases are comprehensively excluded, so international co-operation to conditionally re-open trade and travel between countries certified as free of COVID-19 represents the best strategy for motivating progress towards pandemic eradication at global level. The three sequential goals that every country needs to emphatically embrace are contain, eliminate and exclude. As recently emphasized by the World Health Organization, success will require widespread genuine national unity and unprecedented global solidarity

Predicting Scenarios for Successful Autodissemination of Pyriproxyfen by Malaria Vectors from Their Resting Sites to Aquatic Habitats; Description and Simulation Analysis of a Field-Parameterizable Model

Background Large-cage experiments indicate pyriproxifen (PPF) can be transferred from resting sites to aquatic habitats by Anopheles arabiensis - malaria vector mosquitoes to inhibit emergence of their own offspring. PPF coverage is amplified twice: (1) partial coverage of resting sites with PPF contamination results in far higher contamination coverage of adult mosquitoes because they are mobile and use numerous resting sites per gonotrophic cycle, and (2) even greater contamination coverage of aquatic habitats results from accumulation of PPF from multiple oviposition events. Methods and Findings Deterministic mathematical models are described that use only field-measurable input parameters and capture the biological processes that mediate PPF autodissemination. Recent successes in large cages can be rationalized, and the plausibility of success under full field conditions can be evaluated a priori. The model also defines measurable properties of PPF delivery prototypes that may be optimized under controlled experimental conditions to maximize chances of success in full field trials. The most obvious flaw in this model is the endogenous relationship that inevitably occurs between the larval habitat coverage and the measured rate of oviposition into those habitats if the target mosquito species is used to mediate PPF transfer. However, this inconsistency also illustrates the potential advantages of using a different, non-target mosquito species for contamination at selected resting sites that shares the same aquatic habitats as the primary target. For autodissemination interventions to eliminate malaria transmission or vector populations during the dry season window of opportunity will require comprehensive contamination of the most challenging subset of aquatic habitats that persist or retain PPF activity (Ux) for only one week , where Ux = 7 days). To achieve >99% contamination coverage of these habitats will necessitate values for the product of the proportional coverage of the ovipositing mosquito population with PPF contamination (CM) by the ovitrap-detectable rates of oviposition by wild mosquitoes into this subset of habitats , divided by the titre of contaminated mosquitoes required to render them unproductive , that approximately approach unity . Conclusions The simple multiplicative relationship between CM and , and the simple exponential decay effect they have upon uncontaminated aquatic habitats, allows application of this model by theoreticians and field biologists alike

Mathematical Evaluation of Community Level Impact of Combining Bed Nets and Indoor Residual Spraying upon Malaria Transmission in Areas where the main Vectors are Anopheles Arabiensis Mosquitoes.

Indoor residual insecticide spraying (IRS) and long-lasting insecticide treated nets (LLINs) are commonly used together even though evidence that such combinations confer greater protection against malaria than either method alone is inconsistent. A deterministic model of mosquito life cycle processes was adapted to allow parameterization with results from experimental hut trials of various combinations of untreated nets or LLINs (Olyset, PermaNet 2.0, Icon Life nets) with IRS (pirimiphos methyl, lambda cyhalothrin, DDT), in a setting where vector populations are dominated by Anopheles arabiensis, so that community level impact upon malaria transmission at high coverage could be predicted. Intact untreated nets alone provide equivalent personal protection to all three LLINs. Relative to IRS plus untreated nets, community level protection is slightly higher when Olyset or PermaNet 2.0 nets are added onto IRS with pirimiphos methyl or lambda cyhalothrin but not DDT, and when Icon Life nets supplement any of the IRS insecticides. Adding IRS onto any net modestly enhances communal protection when pirimiphos methyl is sprayed, while spraying lambda cyhalothrin enhances protection for untreated nets but not LLINs. Addition of DDT reduces communal protection when added to LLINs. Where transmission is mediated primarily by An. arabiensis, adding IRS to high LLIN coverage provides only modest incremental benefit (e.g. when an organophosphate like pirimiphos methyl is used), but can be redundant (e.g. when a pyrethroid like lambda cyhalothin is used) or even regressive (e.g. when DDT is used for the IRS). Relative to IRS plus untreated nets, supplementing IRS with LLINs will only modestly improve community protection. Beyond the physical protection that intact nets provide, additional protection against transmission by An. arabiensis conferred by insecticides will be remarkably small, regardless of whether they are delivered as LLINs or IRS. The insecticidal action of LLINs and IRS probably already approaches their absolute limit of potential impact upon this persistent vector so personal protection of nets should be enhanced by improving the physical integrity and durability. Combining LLINs and non-pyrethroid IRS in residual transmission systems may nevertheless be justified as a means to manage insecticide resistance and prevent potential rebound of not only An. arabiensis, but also more potent, vulnerable and historically important species such as Anopheles gambiae and Anopheles funestus