scholarly journals Malaria micro-stratification using routine surveillance data in Western Kenya

2020 ◽  
Author(s):  
Victor A Alegana ◽  
Laurissa Suiyanka ◽  
Peter M Macharia ◽  
Grace Ikahu-Muchangi ◽  
Robert W Snow
Keyword(s):  
Spatial Resolution ◽  
Population Distribution ◽  
Indoor Residual Spraying ◽  
Routine Data ◽  
Malaria Risk ◽  
Health Facilities ◽  
Exceedance Probability ◽  
Future Research ◽  
Small Scale ◽  
Western Kenya

Abstract Background There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya. Methods Routine data from health facilities (n=1,804) representing all ages over 24 months (2018-2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility. Results The overall monthly reporting rate was 78.7% (IQR 75.0-100.0) and public-based health facilities were more likely than private facilities to report ≥12 months (OR 5.7, 95% CI 4.3-7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability >70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability <30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017.Conclusion The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small-scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.

scholarly journals Malaria micro-stratification using routine surveillance data in Western Kenya

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Victor A. Alegana ◽  
Laurissa Suiyanka ◽  
Peter M. Macharia ◽  
Grace Ikahu-Muchangi ◽  
Robert W. Snow
Keyword(s):  
Spatial Resolution ◽  
Population Distribution ◽  
Indoor Residual Spraying ◽  
Routine Data ◽  
Malaria Risk ◽  
Health Facilities ◽  
Exceedance Probability ◽  
Future Research ◽  
Small Scale ◽  
Western Kenya

Abstract Background There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya. Methods Routine data from health facilities (n = 1804) representing all ages over 24 months (2018–2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility. Results The overall monthly reporting rate was 78.7% (IQR 75.0–100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3–7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability > 70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability < 30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017. Conclusion The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small-scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.

scholarly journals Malaria Micro-stratification Using Routine Surveillance Data in Western Kenya

2020 ◽  
Author(s):  
Victor A Alegana ◽  
Laurissa Suiyanka ◽  
Peter M Macharia ◽  
Grace Ikahu-Muchangi ◽  
Robert W Snow
Keyword(s):  
Spatial Resolution ◽  
Population Distribution ◽  
Indoor Residual Spraying ◽  
Routine Data ◽  
Malaria Risk ◽  
Health Facilities ◽  
Exceedance Probability ◽  
Future Research ◽  
Small Scale ◽  
Western Kenya

Abstract Background: There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya. Methods: Routine data from health facilities (n=1804) representing all ages over 24 months (2018-2019) was assembled across 8 countries (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of the health facility.Results: The overall monthly reporting rate was 78.7% (IQR 75.0 – 100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3 – 7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability >70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability <30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017.Conclusion: The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.

scholarly journals Malaria micro-stratification using routine surveillance data in Western Kenya

2020 ◽  
Author(s):  
Victor A Alegana ◽  
Laurissa Suiyanka ◽  
Peter M Macharia ◽  
Grace Ikahu-Muchangi ◽  
Robert W Snow
Keyword(s):  
Spatial Resolution ◽  
Population Distribution ◽  
Indoor Residual Spraying ◽  
Routine Data ◽  
Malaria Risk ◽  
Health Facilities ◽  
Exceedance Probability ◽  
Future Research ◽  
Small Scale ◽  
Western Kenya

Abstract Background: There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya. Methods: Routine data from health facilities (n=1804) representing all ages over 24 months (2018-2019) was assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of the health facility.Results: The overall monthly reporting rate was 78.7% (IQR 75.0 – 100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3 – 7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability >70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability <30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017.Conclusion: The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.

scholarly journals Malaria risk factors in northern Namibia: The importance of occupation, age and mobility in characterizing high-risk populations

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252690
Author(s):  
Jennifer L. Smith ◽  
Davis Mumbengegwi ◽  
Erastus Haindongo ◽  
Carmen Cueto ◽  
Kathryn W. Roberts ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Health Facility ◽  
Latent Class ◽  
Indoor Residual Spraying ◽  
Malaria Risk ◽  
Health Facilities ◽  
Environmental Data ◽  
Behavioral Risk ◽  
Increased Risk

In areas of low and unstable transmission, malaria cases occur in populations with lower access to malaria services and interventions, and in groups with specific malaria risk exposures often away from the household. In support of the Namibian National Vector Borne Disease Program’s drive to better target interventions based upon risk, we implemented a health facility-based case control study aimed to identify risk factors for symptomatic malaria in Zambezi Region, northern Namibia. A total of 770 febrile individuals reporting to 6 health facilities and testing positive by rapid diagnostic test (RDT) between February 2015 and April 2016 were recruited as cases; 641 febrile individuals testing negative by RDT at the same health facilities through June 2016 were recruited as controls. Data on socio-demographics, housing construction, overnight travel, use of malaria prevention and outdoor behaviors at night were collected through interview and recorded on a tablet-based questionnaire. Remotely-sensed environmental data were extracted for geo-located village residence locations. Multivariable logistic regression was conducted to identify risk factors and latent class analyses (LCA) used to identify and characterize high-risk subgroups. The majority of participants (87% of cases and 69% of controls) were recruited during the 2016 transmission season, an outbreak year in Southern Africa. After adjustment, cases were more likely to be cattle herders (Adjusted Odds Ratio (aOR): 4.46 95%CI 1.05–18.96), members of the police or other security personnel (aOR: 4.60 95%CI: 1.16–18.16), and pensioners/unemployed persons (aOR: 2.25 95%CI 1.24–4.08), compared to agricultural workers (most common category). Children (aOR 2.28 95%CI 1.13–4.59) and self-identified students were at higher risk of malaria (aOR: 4.32 95%CI 2.31–8.10). Other actionable risk factors for malaria included housing and behavioral characteristics, including traditional home construction and sleeping in an open structure (versus modern structure: aOR: 2.01 95%CI 1.45–2.79 and aOR: 4.76 95%CI: 2.14–10.57); cross border travel in the prior 30 days (aOR: 10.55 95%CI 2.94–37.84); and outdoor agricultural work at night (aOR: 2.09 95%CI 1.12–3.87). Malaria preventive activities were all protective and included personal use of an insecticide treated net (ITN) (aOR: 0.61 95%CI 0.42–0.87), adequate household ITN coverage (aOR: 0.63 95%CI 0.42–0.94), and household indoor residual spraying (IRS) in the past year (versus never sprayed: (aOR: 0.63 95%CI 0.44–0.90). A number of environmental factors were associated with increased risk of malaria, including lower temperatures, higher rainfall and increased vegetation for the 30 days prior to diagnosis and residing more than 5 minutes from a health facility. LCA identified six classes of cases, with class membership strongly correlated with occupation, age and select behavioral risk factors. Use of ITNs and IRS coverage was similarly low across classes. For malaria elimination these high-risk groups will need targeted and tailored intervention strategies, for example, by implementing alternative delivery methods of interventions through schools and worksites, as well as the use of specific interventions that address outdoor transmission.

scholarly journals An Improved Method of Determining Human Population Distribution Based on Luojia 1-01 Nighttime Light Imagery and Road Network Data—A Case Study of the City of Shenzhen

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5032 ◽  
Author(s):  
Qiang Zhou ◽  
Yuanmao Zheng ◽  
Jinyuan Shao ◽  
Yinglun Lin ◽  
Haowei Wang
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Spatial Resolution ◽  
Urban Population ◽  
Road Network ◽  
Population Distribution ◽  
Small Scale ◽  
Human Settlement ◽  
Nighttime Light ◽  
The City

Previously published studies on population distribution were based on the provincial level, while the number of urban-level studies is more limited. In addition, the rough spatial resolution of traditional nighttime light (NTL) data has limited their fine application in current small-scale population distribution research. For the purpose of studying the spatial distribution of populations at the urban scale, we proposed a new index (i.e., the road network adjusted human settlement index, RNAHSI) by integrating Luojia 1-01 (LJ 1-01) NTL data, the enhanced vegetation index (EVI), and road network density (RND) data based on population density relationships to depict the spatial distribution of urban human settlements. The RNAHSI updated the high-resolution NTL data and combined the RND data on the basis of human settlement index (HSI) data to refine the spatial pattern of urban population distribution. The results indicated that the mean relative error (MRE) between the population estimation data based on the RNAHSI and the demographic data was 34.80%, which was lower than that in the HSI and WorldPop dataset. This index is suitable primarily for the study of urban population distribution, as the RNAHSI can clearly highlight human activities in areas with dense urban road networks and can refine the spatial heterogeneity of impervious areas. In addition, we also drew a population density map of the city of Shenzhen with a 100 m spatial resolution for 2018 based on the RNAHSI, which has great reference significance for urban management and urban resource allocation.

Small-Scale Deliberation and Mass Democracy: A Systematic Review of the Spillover Effects of Deliberative Minipublics

2021 ◽  
pp. 003232172110072
Author(s):  
Ramon van der Does ◽  
Vincent Jacquet
Keyword(s):  
Systematic Review ◽  
Empirical Evidence ◽  
Empirical Research ◽  
Spillover Effects ◽  
Future Research ◽  
Small Scale ◽  
Long Term Effects ◽  
Current Crisis ◽  
Mass Democracy

Deliberative minipublics are popular tools to address the current crisis in democracy. However, it remains ambiguous to what degree these small-scale forums matter for mass democracy. In this study, we ask the question to what extent minipublics have “spillover effects” on lay citizens—that is, long-term effects on participating citizens and effects on non-participating citizens. We answer this question by means of a systematic review of the empirical research on minipublics’ spillover effects published before 2019. We identify 60 eligible studies published between 1999 and 2018 and provide a synthesis of the empirical results. We show that the evidence for most spillover effects remains tentative because the relevant body of empirical evidence is still small. Based on the review, we discuss the implications for democratic theory and outline several trajectories for future research.

scholarly journals Effectiveness of a national mass distribution campaign of long-lasting insecticide-treated nets and indoor residual spraying on clinical malaria in Malawi, 2018–2020

2021 ◽  
Vol 6 (5) ◽  
pp. e005447
Author(s):  
Hillary M Topazian ◽  
Austin Gumbo ◽  
Katerina Brandt ◽  
Michael Kayange ◽  
Jennifer S Smith ◽  
...  
Keyword(s):  
Mass Distribution ◽  
Indoor Residual Spraying ◽  
Malaria Risk ◽  
Bed Nets ◽  
Insecticide Treated Nets ◽  
District Health ◽  
High Transmission ◽  
Limited Effectiveness ◽  
Mass Distribution Campaign ◽  
Distribution Campaign

IntroductionMalawi’s malaria burden is primarily assessed via cross-sectional national household surveys. However, malaria is spatially and temporally heterogenous and no analyses have been performed at a subdistrict level throughout the course of a year. The WHO recommends mass distribution of long-lasting insecticide-treated bed nets (LLINs) every 3 years, but a national longitudinal evaluation has never been conducted in Malawi to determine LLIN effectiveness lifespans.MethodsUsing District Health Information Software 2 (DHIS2) health facility data, available from January 2018 to June 2020, we assessed malaria risk before and after a mass distribution campaign, stratifying by age group and comparing risk differences (RDs) by LLIN type or annual application of indoor residual spraying (IRS).Results711 health facilities contributed 20 962 facility reports over 30 months. After national distribution of 10.7 million LLINs and IRS in limited settings, malaria risk decreased from 25.6 to 16.7 cases per 100 people from 2018 to 2019 high transmission seasons, and rebounded to 23.2 in 2020, resulting in significant RDs of −8.9 in 2019 and −2.4 in 2020 as compared with 2018. Piperonyl butoxide (PBO)-treated LLINs were more effective than pyrethroid-treated LLINs, with adjusted RDs of −2.3 (95% CI −2.7 to −1.9) and −1.5 (95% CI −2.0 to −1.0) comparing 2019 and 2020 high transmission seasons to 2018. Use of IRS sustained protection with adjusted RDs of −1.4 (95% CI −2.0 to −0.9) and −2.8% (95% CI −3.5 to −2.2) relative to pyrethroid-treated LLINs. Overall, 12 of 28 districts (42.9%) experienced increases in malaria risk in from 2018 to 2020.ConclusionLLINs in Malawi have a limited effectiveness lifespan and IRS and PBO-treated LLINs perform better than pyrethroid-treated LLINs, perhaps due to net repurposing and insecticide-resistance. DHIS2 provides a compelling framework in which to examine localised malaria trends and evaluate ongoing interventions.

scholarly journals Insecticide resistance status of Anopheles arabiensis in irrigated and non-irrigated areas in western Kenya

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Pauline Winnie Orondo ◽  
Steven G. Nyanjom ◽  
Harrysone Atieli ◽  
John Githure ◽  
Benyl M. Ondeto ◽  
...  
Keyword(s):  
Insecticide Resistance ◽  
Vector Control ◽  
Anopheles Arabiensis ◽  
Crop Protection ◽  
Indoor Residual Spraying ◽  
Malaria Vectors ◽  
Western Kenya ◽  
Animal Protection ◽  
Selection Of ◽  
Selection Of Resistance

Abstract Background Malaria control in Kenya is based on case management and vector control using long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS). However, the development of insecticide resistance compromises the effectiveness of insecticide-based vector control programs. The use of pesticides for agricultural purposes has been implicated as one of the sources driving the selection of resistance. The current study was undertaken to assess the status and mechanism of insecticide resistance in malaria vectors in irrigated and non-irrigated areas with varying agrochemical use in western Kenya. Methods The study was carried out in 2018–2019 in Homa Bay County, western Kenya. The bioassay was performed on adults reared from larvae collected from irrigated and non-irrigated fields in order to assess the susceptibility of malaria vectors to different classes of insecticides following the standard WHO guidelines. Characterization of knockdown resistance (kdr) and acetylcholinesterase-inhibiting enzyme/angiotensin-converting enzyme (Ace-1) mutations within Anopheles gambiae s.l. species was performed using the polymerase chain reaction (PCR) method. To determine the agricultural and public health insecticide usage pattern, a questionnaire was administered to farmers, households, and veterinary officers in the study area. Results Anopheles arabiensis was the predominant species in the irrigated (100%, n = 154) area and the dominant species in the non-irrigated areas (97.5%, n = 162), the rest being An. gambiae sensu stricto. In 2018, Anopheles arabiensis in the irrigated region were susceptible to all insecticides tested, while in the non-irrigated region reduced mortality was observed (84%) against deltamethrin. In 2019, phenotypic mortality was decreased (97.8–84% to 83.3–78.2%). In contrast, high mortality from malathion (100%), DDT (98.98%), and piperonyl butoxide (PBO)-deltamethrin (100%) was observed. Molecular analysis of the vectors from the irrigated and non-irrigated areas revealed low levels of leucine-serine/phenylalanine substitution at position 1014 (L1014S/L1014F), with mutation frequencies of 1–16%, and low-frequency mutation in the Ace-1R gene (0.7%). In addition to very high coverage of LLINs impregnated with pyrethroids and IRS with organophosphate insecticides, pyrethroids were the predominant chemical class of pesticides used for crop and animal protection. Conclusion Anopheles arabiensis from irrigated areas showed increased phenotypic resistance, and the intensive use of pesticides for crop protection in this region may have contributed to the selection of resistance genes observed. The susceptibility of these malaria vectors to organophosphates and PBO synergists in pyrethroids offers a promising future for IRS and insecticide-treated net-based vector control interventions. These findings emphasize the need for integrated vector control strategies, with particular attention to agricultural practices to mitigate mosquito resistance to insecticides. Graphic abstract

A Critical Review of the Biological Processes in the Chemical Absorption-biological Reduction Integrated System for NO Removal

2021 ◽  
Vol 07 ◽  
Author(s):  
Wei Li
Keyword(s):  
Catalytic Reduction ◽  
Low Cost ◽  
Reduction Process ◽  
Integrated System ◽  
Future Research ◽  
Small Scale ◽  
Biological Processes ◽  
Chemical Absorption ◽  
Biological Reduction ◽  
Biological Reaction

: Exploring low-cost, green and safe technologies to provide an alternative to the conventional selective catalytic reduction process is key to the control of NOx emitted from small-scale boilers and other industrial processes. To meet the demand, the chemical absorption-biological reduction integrated system has been developing recently. chemical absorption-biological reduction integrated system applies Fe(II)EDTA for NO absorption and iron-reducing and denitrifying bacteria for absorbent regeneration. Many studies have focused on the enhancements of mass transfer and biological reaction, among which the biological processes were the rate-limiting steps. This review summarizes the current researches on the biological processes in the CABR system, which focuses on the mechanism and enhancement of biochemical reactions, and provides the possible directions of future research.

scholarly journals Evapotranspiration Estimation with Small UAVs in Precision Agriculture

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6427
Author(s):  
Haoyu Niu ◽  
Derek Hollenbeck ◽  
Tiebiao Zhao ◽  
Dong Wang ◽  
YangQuan Chen
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Spatial Resolution ◽  
Precision Agriculture ◽  
Large Scale ◽  
Bowen Ratio ◽  
Future Research ◽  
Accurate Estimation ◽  
Research Areas ◽  
Energy Balance Approach

Estimating evapotranspiration (ET) has been one of the most critical research areas in agriculture because of water scarcity, the growing population, and climate change. The accurate estimation and mapping of ET are necessary for crop water management. Traditionally, researchers use water balance, soil moisture, weighing lysimeters, or an energy balance approach, such as Bowen ratio or eddy covariance towers to estimate ET. However, these ET methods are point-specific or area-weighted measurements and cannot be extended to a large scale. With the advent of satellite technology, remote sensing images became able to provide spatially distributed measurements. However, the spatial resolution of multispectral satellite images is in the range of meters, tens of meters, or hundreds of meters, which is often not enough for crops with clumped canopy structures, such as trees and vines. Unmanned aerial vehicles (UAVs) can mitigate these spatial and temporal limitations. Lightweight cameras and sensors can be mounted on the UAVs and take high-resolution images. Unlike satellite imagery, the spatial resolution of the UAV images can be at the centimeter-level. UAVs can also fly on-demand, which provides high temporal imagery. In this study, the authors examined different UAV-based approaches of ET estimation at first. Models and algorithms, such as mapping evapotranspiration at high resolution with internalized calibration (METRIC), the two-source energy balance (TSEB) model, and machine learning (ML) are analyzed and discussed herein. Second, challenges and opportunities for UAVs in ET estimation are also discussed, such as uncooled thermal camera calibration, UAV image collection, and image processing. Then, the authors share views on ET estimation with UAVs for future research and draw conclusive remarks.

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