ABSTRACT
"Candidatus Liberibacter asiaticus" (CLas), the causal agent of citrus Huanglongbing (HLB), is able to multiply to a high abundance in citrus fruit pith. However, little is known about the biological processes and phytochemical substances that are vital for CLas colonization and growth in fruit pith. In this study, CLas-infected fruit pith of three citrus cultivars ("Shatangju" mandarin, "Guanxi" pomelo, and "Shatian" pomelo) exhibiting different tolerance to CLas were collected and used for dual RNA-Seq and untargeted metabolome analysis. Comparative transcriptome analysis found that the activation of the CLas noncyclic TCA pathway and pathogenic-related effectors could contribute to the colonization and growth of CLas in fruit pith. The pre-established Type 2 prophage in the CLas genome and the induction of its CRISPR/cas system could enhance the phage resistance of CLas and, in turn, facilitate CLas population growth in fruit pith. CLas infection caused the accumulation of amino acids that were correlated with tolerance to CLas. The accumulation of most sugars and organic acids in CLas-infected fruit pith, which could be due to the phloem blockage caused by CLas infection, was thought to be beneficial for CLas growth in localized phloem tissue. The higher levels of flavonoids and terpenoids in the fruit pith of CLas-tolerant cultivars, particularly those known for their antimicrobial properties, could hinder the growth of CLas. This study advances our understanding of CLas multiplication in fruit pith and offers novel insight into metabolites that could be responsible for tolerance to CLas or essential to CLas population growth.IMPORTANCECitrus Huanglongbing (HLB, also called citrus greening disease) is a highly destructive disease currently threatening citrus production worldwide. HLB is caused by an unculturable bacterial pathogen, "Candidatus Liberibacter asiaticus" (CLas). However, the mechanism of CLas colonization and growth in citrus hosts is poorly understood. In this study, we utilized the fruit pith tissue, which was able to maintain the CLas at a high abundance, as the materials for dual RNA-Seq and untargeted metabolome analysis, aiming to reveal the biological processes and phytochemical substances that are vital for CLas colonization and growth. We provided a genome-wide CLas transcriptome landscape in the fruit pith of three citrus cultivars with different tolerance and identified the important genes/pathways that contribute to CLas colonization and growth in the fruit pith. Metabolome profiling identified the key metabolites, which were mainly affected by CLas infection and influenced the population dynamic of CLas in fruit pith.
Subject(s)
Citrus , Liberibacter , Rhizobiaceae , Citrus/microbiology , Rhizobiaceae/genetics , Rhizobiaceae/metabolism , Transcriptome , Fruit/metabolism , Metabolome , Population Dynamics , Phytochemicals/metabolism , Plant Diseases/microbiologyABSTRACT
BACKGROUND: To compare text messaging and face-to-face interviews to conduct a survey on childhood diarrhoea and pneumonia. METHODS: Caregivers of young children able to send text messages in Zhao County in rural China were included in this crossover study. Villages (clusters) were randomized into two groups using the ratio 1:1.6 to account for an expected higher drop-out in group 2. In group 1, participants first completed the face-to-face and then text messaging survey; this order was reversed in group 2. We determined data equivalence of 17 questions that were answered by participants who were the same person in both surveys. For the text messaging survey, we assessed the overall and item response rate. RESULTS: We included 1014 participants between 16 and 28 March 2013: 371 in 15 villages in group 1 and 643 in 27 villages in group 2. A total of 662 (65.3%) out of 1014 participants responded (first text message question) and a significantly higher proportion who did not respond were from rural areas (P = 0.005). Of 651 participants willing to participate, 356 (54.7%) completed the text messaging survey, which was marginally significantly different between the groups (P = 0.05). In total, 409 participants took part in both surveys: 183 in group 1 and 226 in group 2. There was a significantly higher proportion of caregivers from rural areas in Zhao County in the non-responder group compared to the responder group (P = 0.004). Kappas were substantial for six (0.61-0.80), moderate for two (0.58 and 0.60), and fair for three questions (0.31, 0.35 and 0.37). The proportion of agreement was >90% for five questions; 80.0%-90.0% for five questions; 70.0%, 65.0% and 45.5%. The remaining questions had too small numbers to calculate these values. CONCLUSIONS: This study shows that text messaging data collection produces data similar to data from face-to-face interviews in a middle-income setting, but the response rate was insufficient for use in public health surveys. Improving the response rate is important, because text message surveys could be of greater value in rural remote areas due to the cost-saving potential.
Subject(s)
Diarrhea/therapy , Health Surveys/methods , Interviews as Topic , Pneumonia/therapy , Text Messaging , Caregivers/psychology , Caregivers/statistics & numerical data , Child, Preschool , China , Cluster Analysis , Cross-Over Studies , Female , Humans , Infant , Infant, Newborn , Male , Patient Acceptance of Health Care , Rural Population/statistics & numerical dataABSTRACT
BACKGROUND: Large investments are currently made in community-based complementary food supplement (Ying Yang Bao, YYB) programs to improve nutrition of young children in rural areas in China. However, there is a lack of knowledge about the experience and challenges of implementing YYB programs in China. We aimed to: 1) monitor distribution of YYB; 2) assess children's adherence to and acceptability of YYB; and 3) evaluate community-based strategies to improve the program. METHODS: This mixed methods evaluation study combined data from surveys and focus groups that took place during a controlled interventional evaluation trial. The trial aimed to evaluate the effectiveness of community-based YYB distribution on improving children's health status in rural areas in China. We conducted five cross-sectional surveys with caregivers of children aged 6-23 months (baseline survey (N = 1804) in August 2012 and four follow-up cross-sectional surveys: 1) N = 494 in January 2013; 2) N = 2187 in August 2013; 3) N = 504 in January 2014; and 4) N = 2186 in August 2014) in one rural county in Qinghai Province. We used a two-stage cluster sampling technique to select mothers with eligible children for each survey. Information was collected from caregivers on household characteristics, YYB consumption and acceptability in the surveys. High adherence in each survey was defined as children who consumed at least four YYB sachets during the previous week. A logistic regression model was developed to obtain odds ratios (OR) with 95% confidence intervals of factors associated with high adherence. Also, we conducted 10 focus groups with73 caregivers and health workers involved in the YYB distribution. Content analysis was used to explore qualitative findings, which were used to gain deeper insight into the quantitative results. RESULTS: Around 90% of caregivers had ever received YYB and more than 80% of children ever took YYB. Caregivers mainly knew about YYB through their village doctors. High adherence to YYB increased from 49.4% in the first follow-up survey (January 2013) to 81.4% in the last follow-up survey (August 2014; P < 0.0001). Repeated training sessions with village doctors could increase adherence. However, due to unplanned YYB stock-out, caregivers did not receive YYB for six months, which may have led to a decrease of high adherence from 64.1% in the second follow-up survey (August 2013) to 53.6% in the third follow-up survey (January 2014; P < 0.0001). Self-reported acceptability increased from 43.2% to 71.8%, partly due to improving the taste of YYB, which was the main reason that children disliked taking YYB. Unfortunately, more than 60% of caregivers did not perceive positive health improvement in their children after taking YYB. Multivariate analysis showed that children with diarrhea (OR = 1.216, 95% CI 1.025-1.442), cough or fever (OR = 1.222, 95% CI 1.072-1.393) during the past two weeks had significantly lower adherence. CONCLUSIONS: This evaluation study showed that program monitoring in rural West China was critically important for understanding program implementation and adherence trends. This led to strategic changes to the intervention over time: improving the taste of YYB; strengthening health education of village doctors and caregivers; and ensuring continuity of YYB supply. Future programs need to monitor program implementation in other settings in China and elsewhere.
Subject(s)
Caregivers/psychology , Dietary Supplements/statistics & numerical data , Patient Compliance/statistics & numerical data , Rural Population , China , Cross-Sectional Studies , Dietary Supplements/supply & distribution , Focus Groups , Humans , Infant , Program Evaluation , Surveys and QuestionnairesABSTRACT
BACKGROUND: The aim of this study was to assess the effectiveness of an EPI smartphone application (EPI app) on improving vaccination coverage in rural Sichuan Province, China. METHODS: This matched-pair cluster randomized controlled study included 32 village doctors, matched in 16 pairs, and took place from 2013 to 2015. Village doctors in the intervention group used the EPI app and reminder text messages while village doctors in the control group used their usual procedures and text messages. The primary outcome was full vaccination coverage with all five vaccines (1 dose of BCG, 3 doses of hepatitis B, 3 doses of OPV, 3 doses of DPT and 1 dose of measles vaccine), and the secondary outcome was coverage with each dose of the five individual vaccines. We also conducted qualitative interviews with village doctors to understand perceptions on using the EPI app and how this changed their vaccination work. RESULTS: The full vaccination coverage increased statistically significant from baseline to end-line in both the intervention (67 % [95 % CI:58-75 %] to 84 % [95 % CI:76-90 %], P = 0.028) and control group (71 % [95 % CI:62-79 %] to 82 % [95 % CI:74-88 %], P = 0.014). The intervention group had higher increase in full vaccination coverage from baseline to end-line compared to the control group (17 % vs 10 %), but this was not statistically significant (P = 0.164). Village doctors found it more convenient to use the EPI app to manage child vaccination and also reported saving time by looking up information of caregivers and contacting caregivers for overdue vaccinations quicker. However, village doctors found it hard to manage children who migrated out of the counties. CONCLUSIONS: This study showed that an app and text messages can be used by village doctors to improve full vaccination coverage, though no significant increase in vaccination coverage was found when assessing the effect of the app on its own. Village doctors using EPI app reported having improved their working efficiency of managing childhood vaccination. Future studies should be conducted to evaluate the impact of more integrated approach of mHealth intervention on child immunization. TRIAL REGISTRATION: Chinese Clinical Trials Registry (ChiCTR): ChiCTR-TRC- 13003960 , registered on December 6, 2013.
Subject(s)
Immunization Programs/methods , Immunization/statistics & numerical data , Mobile Applications , Program Evaluation/statistics & numerical data , Rural Health Services , Child , Child, Preschool , China , Cluster Analysis , Female , Humans , Male , SmartphoneABSTRACT
INTRODUCTION: To capitalise on mHealth, we need to understand the use of mobile phones both in daily life and for health care. OBJECTIVE: To assess the prevalence and factors that influence usage of mobile phones by caregivers of young children. MATERIALS AND METHODS: A mixed methods approach was used, whereby a survey (N=1854) and semi-structured interviews (N=17) were conducted concurrently. The quantitative and qualitative data obtained were compared and integrated. Participants were caregivers of young children in Zhao County, Hebei Province, China. RESULTS: Four main themes were found: (i) trends in mobile phone ownership; (ii) usage of mobile phone functions; (iii) factors influencing replying to text messages; and (iv) uses of mobile phones for health care. The majority of 1,854 survey participants (1,620; 87.4%) used mobile phones, but usage was much higher among mothers (1,433; 92.6%) and fathers (41; 100.0%) compared to grandparents (142; 54.6%). Parents were able to send text messages, grandparents often not. Factors influencing the decision to reply to text messages in daily life were checking the mobile phone, trusting the sender, emotion or feeling when receiving a text message, the importance of replying and ease of use of text messages. Of 1,620 survey participants who used a mobile phone, about one in four (432; 26.7%) had used it for health care in the past three months and most (1,110; 93.5%) of 1,187 who had not wished to use their phone to receive health information. CONCLUSION: We found that usage of mobile phones is high, several factors influencing usage and an interest of caregivers to use phones for health care in Zhao County, rural China, which can be used to inform studies in settings with similar characteristics. Future work needs to assess factors influencing mobile phone usage in-depth to optimize experiences of users for specific mHealth-based interventions.
Subject(s)
Caregivers , Cell Phone/statistics & numerical data , Rural Population , Telemedicine/statistics & numerical data , Adult , China , Delivery of Health Care , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Young AdultABSTRACT
OBJECTIVE: To test the effectiveness of multiple interventions on increasing the response rate of text messaging for longitudinal data collection. METHODS: Our cohort included 283 caregivers of children aged 6-12â months who were participating in an anemia program in rural China. Using text messages to collect data on anemia medication adherence, we conducted a delayed randomized controlled trial to test multiple interventions (an additional four reminders; a ¥5.0 (US$0.79) credit reward for replying; and a feedback text message). After a 6-week pilot study with week 7 as the baseline measurement, we randomly allocated all participants into two groups: group 1 (n = 142) and group 2 (n = 141). During weeks 8-11, we introduced the interventions to group 1, and in weeks 12-15 the intervention was introduced to both groups. We compared the response rates between groups and explored factors affecting the response rate. RESULTS: During weeks 8-11, the response rates in group 1 increased and were significantly higher than in group 2 (p<0.05). During weeks 12-15, the response rate increased significantly in group 2 (p>0.05) and slightly decreased in group 1. Younger participants or participants who had children with lower hemoglobin concentration were more likely to reply (p = 0.02). Sending four reminders on the second day contributed to only 286 (11.7%) extra text messages. DISCUSSION: Our study showed that multiple interventions were effective in increasing response rate of text messaging data collection in rural China. CONCLUSIONS: Larger multi-site studies are needed to find the most effective way of using these interventions to allow usage of text messaging data collection for health research.
Subject(s)
Data Collection/methods , Text Messaging , Adult , Anemia/drug therapy , Caregivers , China , Female , Humans , Infant , Interviews as Topic , Male , Pilot Projects , Rural Population , Time FactorsABSTRACT
BACKGROUND: Although good progress has been achieved in expanding immunization of children in China, disparities exist across different provinces. Information gaps both from the service supply and demand sides hinder timely vaccination of children in rural areas. The rapid development of mobile health technology (mHealth) provides unprecedented opportunities for improving health services and reaching underserved populations. However, there is a lack of literature that rigorously evaluates the impact of mHealth interventions on immunization coverage as well as the usability and feasibility of smart phone applications (apps). This study aims to assess the effectiveness of a smart phone-based app (Expanded Program on Immunization app, or EPI app) on improving the coverage of children's immunization. METHODS/DESIGN: This cluster randomized trial will take place in Xuanhan County, Sichuan Province, China. Functionalities of the app include the following: to make appointments automatically, record and update children's immunization information, generate a list of children who missed their vaccination appointments, and send health education information to village doctors. After pairing, 36 villages will be randomly allocated to the intervention arm (n=18) and control arm (n=18). The village doctors in the intervention arm will use the app while the village doctors in the control arm will record and manage immunization in the usual way in their catchment areas. A household survey will be used at baseline and at endline (8 months of implementation). The primary outcome is full-dose coverage and the secondary outcome is immunization coverage of the five vaccines that are included in the national Expanded Program on Immunization program as well as Hib vaccine, Rotavirus vaccine and Pneumococcal conjugate vaccine. Multidimensional evaluation of the app will also be conducted to assess usability and feasibility. DISCUSSION: This study is the first to evaluate the effectiveness of a smart phone app for child immunization in rural China. This study will contribute to the knowledge about the usability and feasibility of a smart phone app for managing immunization in rural China and to similar populations in different settings. TRIAL REGISTRATION: Chinese Clinical Trials Registry (ChiCTR): ChiCTR-TRC-13003960.
Subject(s)
Cell Phone/statistics & numerical data , Immunization Programs/methods , Immunization Programs/statistics & numerical data , Immunization/methods , Immunization/statistics & numerical data , Rural Population/statistics & numerical data , China , Cluster Analysis , Female , Health Services Accessibility/statistics & numerical data , Humans , Infant , Male , Program Evaluation/methods , Program Evaluation/statistics & numerical data , Rural Health/statistics & numerical dataABSTRACT
BACKGROUND: We set up a collaboration between researchers in China and the UK that aimed to explore the use of mHealth in China. This is the first paper in a series of papers on a large mHealth project part of this collaboration. This paper included the aims and objectives of the mHealth project, our field site, and the detailed methods of two studies. FIELD SITE: The field site for this mHealth project was Zhao County, which lies 280 km south of Beijing in Hebei Province, China. METHODS: WE DESCRIBED THE METHODOLOGY OF TWO STUDIES: (i) a mixed methods study exploring factors influencing sample size calculations for mHealth-based health surveys and (ii) a cross-over study determining validity of an mHealth text messaging data collection tool. The first study used mixed methods, both quantitative and qualitative, including: (i) two surveys with caregivers of young children, (ii) interviews with caregivers, village doctors and participants of the cross-over study, and (iii) researchers' views. We combined data from caregivers, village doctors and researchers to provide an in-depth understanding of factors influencing sample size calculations for mHealth-based health surveys. The second study, a cross-over study, used a randomised cross-over study design to compare the traditional face-to-face survey method to the new text messaging survey method. We assessed data equivalence (intrarater agreement), the amount of information in responses, reasons for giving different responses, the response rate, characteristics of non-responders, and the error rate. CONCLUSIONS: This paper described the objectives, field site and methods of a large mHealth project part of a collaboration between researchers in China and the UK. The mixed methods study evaluating factors that influence sample size calculations could help future studies with estimating reliable sample sizes. The cross-over study comparing face-to-face and text message survey data collection could help future studies with developing their mHealth tools.
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BACKGROUND: Effective interventions in maternal, newborn and child health (MNCH), if achieving high level of population coverage, could prevent most of deaths in children under five years of age. High-quality measurements of MNCH coverage are essential for tracking progress and making evidence-based decisions. METHODS: MNCH coverage data are mainly collected through fieldworkers' interview with preselected households in standard programs of Demographic and Health Surveys (DHS) or Multiple Indicator Cluster Surveys (MICS) in most low- and middle-income countries. Household surveys will continue to be the major data source for MNCH coverage in the foreseeable future. However, face-to-face data collection broadly used in household surveys is labor-intensive, time-consuming and expensive. Mobile phones are drawing more and more interest in medical research with the rapid increase in usage and text messaging could be an innovative way of data collection, that is, we could collect DHS data through mHealth method. We refer to it as "mDHS". FINDING: We propose in this paper a conceptual model for measuring MNCH coverage by text messaging in China. In developing this model, we considered resource constraints, sample representativeness, sample size and survey bias. The components of the model are text messaging platform, routine health information system, health facilities, communities and households. CONCLUSIONS: Measuring MNCH interventions coverage by text messaging could be advantageous in many ways and establish a much larger evidence-base for MNCH health policies in China. Before mDHS could indeed be launched, research priorities would include a systematic assessment of routine health information systems and exploring feasibility to collect name lists, mobile phone numbers and general demographic and socio-economic data; qualitative interviews with health workers and caregivers; assessment of data validity of all indicators to be collected by text messaging; and exploring approaches to increase participation rate.
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BACKGROUND: Face-to-face interviews by trained field workers are commonly used in household surveys. However, this data collection method is labor-intensive, time-consuming, expensive, prone to interviewer and recall bias and not easily scalable to increase sample representativeness. OBJECTIVE: To explore the feasibility of using text messaging to collect information on infant and young child feeding practice in rural China. METHODS: Our study was part of a clustered randomized controlled trial that recruited 591 mothers of children aged 12 to 29 months in rural China. We used the test-retest method: first we collected data through face-to-face interviews and then through text messages. We asked the same five questions on standard infant and young child feeding indicators for both methods and asked caregivers how they fed their children yesterday. We assessed the response rate of the text messaging method and compared data agreement of the two methods. FINDING: In the text messaging survey, the response rate for the first question and the completion rate were 56.5% and 48.7%, respectively. Data agreement between the two methods was excellent for whether the baby was breastfed yesterday (question 1) (kappa, κ = 0.81), moderate for the times of drinking infant formula, fresh milk or yoghurt yesterday (question 2) (intraclass correlation coefficient, ICC = 0.46) and whether iron fortified food or iron supplement was consumed (question 3) (κ = 0.44), and poor for 24-hour dietary recall (question 4) (ICC = 0.13) and times of eating solid and semi-solid food yesterday (question 5) (ICC = 0.06). There was no significant difference in data agreement between the two surveys at different time intervals. For infant and young child feeding indicators from both surveys, continued breastfeeding at 1 year (P = 1.000), continued breastfeeding at 2 years (P = 0.688) and minimum meal frequency (P = 0.056) were not significantly different, whereas minimum dietary diversity, minimum accepted diet and consumption of iron-rich or iron fortified foods were significantly different (P < 0.001). CONCLUSIONS: The response rate for our text messaging survey was moderate compared to response rate of other studies using text messaging method and the data agreement between the two methods varied for different survey questions and infant and young child feeding indicators. Future research is needed to increase the response rate and improve data validity of text messaging data collection.
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BACKGROUND: An important issue for mHealth evaluation is the lack of information for sample size calculations. OBJECTIVE: To explore factors that influence sample size calculations for mHealth-based studies and to suggest strategies for increasing the participation rate. METHODS: We explored factors influencing recruitment and follow-up of participants (caregivers of children) in an mHealth text messaging data collection cross-over study. With help of village doctors, we recruited 1026 (25%) caregivers of children under five out of the 4170 registered. To explore factors influencing recruitment and provide recommendations for improving recruitment, we conducted semi-structured interviews with village doctors. Of the 1014 included participants, 662 (65%) responded to the first question about willingness to participate, 538 (53%) responded to the first survey question and 356 (35%) completed the text message survey. To explore factors influencing follow-up and provide recommendations for improving follow-up, we conducted interviews with participants. We added views from the researchers who were involved in the study to contextualize the findings. RESULTS: WE FOUND SEVERAL FACTORS INFLUENCING RECRUITMENT RELATED TO THE FOLLOWING THEMES: experiences with recruitment, village doctors' work, village doctors' motivations, caregivers' characteristics, caregivers' motivations. Village doctors gave several recommendations for ways to recruit more caregivers and we added our views to these. We found the following factors influencing follow-up: mobile phone usage, ability to use mobile phone, problems with mobile phone, checking mobile phone, available time, paying back text message costs, study incentives, subjective norm, culture, trust, perceived usefulness of process, perceived usefulness of outcome, perceived ease of use, attitude, behavioural intention to use, and actual use. From our perspective, factors influencing follow-up were: different caregivers participating in face-to-face and text message survey, sending text messages manually, participants responding incorrectly, and technical issues. Participants provided several recommendations for improving follow-up and we added our views to these. CONCLUSIONS: This is the first study to evaluate factors influencing recruitment and follow-up of participants in an mHealth study in a middle-income setting. More work is needed to assess effectiveness of our suggested strategies. This work would improve evaluation of mHealth interventions.
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BACKGROUND: An effective data collection method is crucial for high quality monitoring of health interventions. The traditional face-to-face data collection method is labor intensive, expensive, and time consuming. With the rapid increase of mobile phone subscribers, text messaging has the potential to be used for evaluation of population health interventions in rural China. OBJECTIVE: The objective of this study was to explore the feasibility of using text messaging as a data collection tool to monitor an infant feeding intervention program. METHODS: Participants were caregivers of children aged 0 to 23 months in rural China who participated in an infant feeding health education program. We used the test-retest method. First, we collected data with a text messaging survey and then with a face-to-face survey for 2 periods of 3 days. We compared the response rate, data agreement, costs, and participants' acceptability of the two methods. Also, we interviewed participants to explore their reasons for not responding to the text messages and the reasons for disagreement in the two methods. In addition, we evaluated the most appropriate time during the day for sending text messages. RESULTS: We included 258 participants; 99 (38.4%) participated in the text messaging survey and 177 (68.6%) in the face-to-face survey. Compared with the face-to-face survey, the text messaging survey had much lower response rates to at least one question (38.4% vs 68.6%) and to all 7 questions (27.9% vs 67.4%) with moderate data agreement (most kappa values between .5 and .75, the intraclass correlation coefficients between .53 to .72). Participants who took part in both surveys gave the same acceptability rating for both methods (median 4.0 for both on a 5-point scale, 1=disliked very much and 5=liked very much). The costs per questionnaire for the text messaging method were much lower than the costs for the face-to-face method: ¥19.7 (US $3.13) versus ¥33.9 (US $5.39) for all questionnaires, and ¥27.1 (US $4.31) versus ¥34.4 (US $5.47) for completed questionnaires. The main reasons for not replying were that participants did not receive text messages, they were too busy to reply, or they did not see text messages in time. The main reasons for disagreement in responses were that participants forgot their answers in the text messaging survey and that they changed their minds. We found that participants were more likely to reply to text messages immediately during 2 time periods: 8 AM to 3 PM and 8 PM to 9 PM. CONCLUSIONS: The text messaging method had reasonable data agreement and low cost, but a low response rate. Further research is needed to evaluate effectiveness of measures that can increase the response rate, especially in collecting longitudinal data by text messaging.