Effects of COVID-19 government travel restrictions on mobility in a rural border area of Northern Thailand: A mobile phone tracking study

An overlooked poultry trade network of the smallholder farms in the border provinces of Thailand, 2021: implications for avian influenza surveillance

Introduction

In Thailand, community-level poultry trade is conducted on a small-scale involving farmers and traders with many trade networks. Understanding the poultry movements may help identify different activities that farmers and traders might contribute to the spread of avian influenza.

Methods

This study aimed to describe the characteristics of players involved in the poultry trade network at the northeastern border of Thailand using network analysis approaches. Mukdahan and Nakhon Phanom provinces, which border Laos, and Ubon Ratchathani province, which borders both Laos and Cambodia, were selected as survey sites.

Results

Local veterinary officers identified and interviewed 338 poultry farmers and eight poultry traders in 2021. A weighted directed network identified incoming and outgoing movements of where the subdistricts traded chickens. Ninety-nine subdistricts and 181 trade links were captured. A self-looping (trader and consumer in the same subdistrict) feedback was found in 56 of 99 subdistricts. The median distance of the movements was 14.02 km (interquartile range (IQR): 6.04-102.74 km), with a maximum of 823.08 km. Most subdistricts in the network had few poultry trade connections, with a median of 1. They typically connected to 1-5 other subdistricts, most often receiving poultry from 1 to 2.5 subdistricts, and sending to 1-2 subdistricts. The subdistricts with the highest overall and in-degree centrality were located in Mukdahan province, whereas one with the highest out-degree centrality was found in Nakhon Phanom province.

Discussion

The poultry movement pattern observed in this network helps explain how avian influenza could spread over the networks once introduced.

Human movement patterns of farmers and forest workers from the Thailand-Myanmar border

Background: Human travel patterns play an important role in infectious disease epidemiology and ecology. Movement into geographic spaces with high transmission can lead to increased risk of acquiring infections. Pathogens can also be distributed across the landscape via human travel. Most fine scale studies of human travel patterns have been done in urban settings in wealthy nations. Research into human travel patterns in rural areas of low- and middle-income nations are useful for understanding the human components of epidemiological systems for malaria or other diseases of the rural poor. The goal of this research was to assess the feasibility of using GPS loggers to empirically measure human travel patterns in this setting, as well as to quantify differing travel patterns by age, gender, and seasonality among study participants. Methods: In this pilot study we recruited 50 rural villagers from along the Myanmar-Thailand border to carry GPS loggers for the duration of a year. The GPS loggers were programmed to take a time-stamped reading every 30 minutes. We calculated daily movement ranges and multi-day trips by age and gender. We incorporated remote sensing data to assess patterns of days and nights spent in forested or farm areas, also by age and gender. Results: Our study showed that it is feasible to use GPS devices to measure travel patterns, though we had difficulty recruiting women and management of the project was relatively intensive. We found that older adults traveled farther distances than younger adults and adult males spent more nights in farms or forests. Conclusion: The results of this study suggest that further work along these lines would be feasible in this region. Furthermore, the results from this study are useful for individual-based models of disease transmission and land use.

COVID-19 is linked to changes in the time-space dimension of human mobility

Socio-economic constructs and urban topology are crucial drivers of human mobility patterns. During the coronavirus disease 2019 pandemic, these patterns were reshaped in their components: the spatial dimension represented by the daily travelled distance, and the temporal dimension expressed as the synchronization time of commuting routines. Here, leveraging location-based data from de-identified mobile phone users, we observed that, during lockdowns restrictions, the decrease of spatial mobility is interwoven with the emergence of asynchronous mobility dynamics. The lifting of restriction in urban mobility allowed a faster recovery of the spatial dimension compared with the temporal one. Moreover, the recovery in mobility was different depending on urbanization levels and economic stratification. In rural and low-income areas, the spatial mobility dimension suffered a more considerable disruption when compared with urbanized and high-income areas. In contrast, the temporal dimension was more affected in urbanized and high-income areas than in rural and low-income areas.

Risk Perception, Perceived Government Coping Validity, and Individual Response in the Early Stage of the COVID-19 Pandemic in China

As a major crisis event, the COVID-19 pandemic has affected the global economy, threatened the lives of the public, and caused varying degrees of impact on the public. Previous studies have shown that risk perception and government response had different impacts on the public, but they revealed more about the independent impact of risk perception and government response on the public. This study will comprehensively consider the impacts of these two factors on the behavior of the public in the early stage of the epidemic. We analyzed data from an online survey in the early days of the COVID-19 pandemic in China and categorized individual behaviors into three dimensions: entertainment and travel, work, and the stockpile of supplies. In addition, we defined the risk perception variables by two dimensions: knowledge of the epidemic itself and knowledge of the consequences of the epidemic. At the same time, we used an exploratory factor analysis to construct the variable of perceived government coping validity and then adopted the ordinal logit model for analysis. The results showed that in terms of entertainment and travel, people would not be affected even if they fully understood the epidemic itself; once they were aware of the negative social consequences of the epidemic, people would suspend entertainment and travel to prevent the spread of the virus. As for work or employment, people would not stop working or employment even if they realized the infectivity and harmfulness of the disease and its social consequences. Furthermore, fear of COVID-19 and the perception of uncontrolled COVID-19 significantly positively affected people's material stockpiling behavior. These results indicate that different risk perceptions had different effects on individual responses, and individual behaviors reflected different coping logics. In addition, the government's effective response to the epidemic would significantly reduce the negative impacts of the epidemic on the three dimensions of people's responses. These conclusions have certain policy implications for preventing and responding to outbreaks in other countries.

Changes in mobility amid the COVID-19 pandemic in Sapporo City, Japan: An investigation through the relationship between spatiotemporal population density and urban facilities

By the end of 2021, the Omicron variant of coronavirus disease 2019 had become the dominant cause of a worldwide pandemic crisis. This demands a deeper analysis to support policy makers in creating interventions that not only protect people from the pandemic but also remedy its negative effects on the economy. Thus, this study investigated people's mobility changes through the relationship between spatiotemporal population density and urban facilities. Results showed that places related to daily services, restaurants, commercial areas, and offices experienced decreased visits, with the highest decline belonging to commercial facilities. Visits to health care and production facilities were stable on weekdays but increased on holidays. Educational institutions' visits decreased on weekdays but increased on holidays. People's visits to residential housing and open spaces increased, with the rise in residential housing visits being more substantial. The results also confirmed that policy interventions (e.g., declaration of emergency and upgrade of restriction level) have a great impact on people's mobility in the short term. The findings would seem to indicate that visit patterns at service and restaurant places decreased least during the pandemic. The analysis outcomes suggest that policy makers should pay more attention to risk perception enhancement as a long-term measure. Furthermore, the study clarified the population density of each facility type in a time series. Improving model performance would be promising for tracking and predicting the spread of future pandemics.

Mobility in informal settlements during a public lockdown: A case study in South Africa

Many African countries quickly responded to the COVID-19 pandemic in 2020 with lockdowns of public life. Yet, many have large numbers of dense informal settlements where infrastructure is shared, houses are small, and residents live on low incomes. These conditions make complying with curfews extraordinarily difficult. Using pedestrian motion sensors installed throughout an informal settlement in Cape Town, South Africa, we study how the lockdown affected mobility in the evenings, early mornings, and during the nights between February 14 and June 18, 2020. We find that mobility was already decreasing in March prior to the start of lockdown by 23% in paths-about half of the overall decline-and by 19% in shared courtyards. Starting with the lockdown on March 27, pedestrian activity decreased by 48% in comparison to February 2020 across paths and by 61% in shared courtyards. We notice the biggest changes on weekends, normally key leisure times, and between 6:00 pm and 9:00 pm and between 6:00 am and 8:00 am, spanning typical commute hours, though these hours continue to have the most activity indicating some people continue to commute. The results show that mobility reduction is large, though generally smaller than reductions observed in high-income countries. We find that residents of informal settlements comply with state-mandated lockdowns to the best of their ability given the circumstances, but that awareness of COVID-19 with less strict regulations prior to lockdown also led to mobility declines.

Estimating the potential overdiagnosis and overtreatment of acute appendicitis in Thailand using a secondary data analysis of service utilization before, during and after the COVID-19 lockdown policy

Introduction

Acute appendicitis is one of the most common surgical emergencies; however, optimal diagnosis and treatment of acute appendicitis remains challenging. We used the coronavirus disease 2019 (COVID-19) lockdown policy as a natural experiment to explore potential overdiagnosis and overtreatment of acute appendicitis in Thailand. The aim of this study was to estimate the potential overdiagnosis and overtreatment of acute appendicitis in Thailand by examining service utilization before, during, and after the COVID-19 lockdown policy.

Methods

A secondary data analysis of patients admitted with acute appendicitis under the Universal Coverage Scheme (UCS) in Thailand over a 6-year period between 2016 and 2021 was conducted. The trend of acute appendicitis was plotted using a 14-day rolling average of daily cases. Patient characteristics, clinical management, and outcomes were descriptively presented and compared among three study periods, namely pre-pandemic, lockdown, and post-lockdown.

Results

The number of overall acute appendicitis cases decreased from 25,407 during pre-pandemic to 22,006 during lockdown (13.4% reduction) and 21,245 during post-lockdown (16.4% reduction). This reduction was mostly due to a lower incidence of uncomplicated acute appendicitis, whereas cases of generalized peritonitis were scarcely affected by the pandemic. There was an increasing trend towards the usage of diagnostic computerized tomography for acute appendicitis but no significant difference in treatment modalities and complication rates.

Conclusion

The stable rates of generalized peritonitis and complications during the COVID-19 lockdown, despite fewer admissions overall, suggest that there may have been overdiagnosis and overtreatment of acute appendicitis in Thailand. Policy makers could use these findings to improve clinical practice for acute appendicitis in Thailand and support the efficient utilization of surgical services in the future, especially during pandemics.

Malaria Research for Tailored Control and Elimination Strategies in the Greater Mekong Subregion

The malaria landscape in the Greater Mekong Subregion has experienced drastic changes with the ramp-up of the control efforts, revealing formidable challenges that slowed down the progress toward malaria elimination. Problems such as border malaria and cross-border malaria introduction, multidrug resistance in Plasmodium falciparum, the persistence of Plasmodium vivax, the asymptomatic parasite reservoirs, and insecticide resistance in primary vectors require integrated strategies tailored for individual nations in the region. In recognition of these challenges and the need for research, the Southeast Asian International Center of Excellence for Malaria Research has established a network of researchers and stakeholders and conducted basic and translational research to identify existing and emerging problems and develop new countermeasures. The installation of a comprehensive disease and vector surveillance system at sentinel sites in border areas with the implementation of passive/active case detection and cross-sectional surveys allowed timely detection and management of malaria cases, provided updated knowledge for effective vector control measures, and facilitated the efficacy studies of antimalarials. Incorporating sensitive molecular diagnosis to expose the significance of asymptomatic parasite reservoirs for sustaining transmission helped establish the necessary evidence to guide targeted control to eliminate residual transmission. In addition, this program has developed point-of-care diagnostics to monitor the quality of artemisinin combination therapies, delivering the needed information to the drug regulatory authorities to take measures against falsified and substandard antimalarials. To accelerate malaria elimination, this program has actively engaged with stakeholders of all levels, fostered vertical and horizontal collaborations, and enabled the effective dissemination of research findings.

Co-Infection with Plasmodium vivax and COVID-19 in Thailand

With the emergence of SARS-CoV-2, healthcare systems not only had to address the pressing clinical needs of the COVID-19 pandemic but anticipate the effect on and of other conditions and diseases. This was of particular concern in areas of the world endemic with malaria, a disease which takes hundreds of thousands of lives each year. This case report from Thailand describes a 25-year-old man diagnosed with Plasmodium vivax, who was then found to be co-infected with COVID-19. Both conditions can have overlapping acute febrile illness symptoms which may delay or complicate diagnoses. He had no prior history of malaria and had received two vaccinations against COVID-19. His clinical course was mild with no pulmonary complications or oxygen requirement, and he responded well to treatments for both conditions. Three months after cure, he again contracted COVID-19 but did not experience any P. vivax relapse. Review of the available literature produced less than 10 publications describing co-infections with P. vivax and COVID-19; nonetheless, in endemic areas, vigilance for both diseases should continue, as co-infections could significantly alter the course of clinical management and prognosis as well as affect the healthcare staff caring for these patients.

A Study on the Decay Model of Multi-Block Taxi Travel Demand under the Influence of Major Urban Public Health Events

A sudden major public health event is likely to have a negative impact on public transport travel for residents, with public travel modes such as the metro and conventional buses experiencing varying degrees of decline in patronage. As a complement to public transport, taxi travel will suffer the same impact. Land use and population density among various functional blocks in a city are different, and therefore their changing rates in taxi travel demand are varied. This paper reveals the taxi travel demand correlations between urban blocks and then constructs a taxi travel demand decay model based on the Dynamic Input-Output Inoperability Model (DIIM) to simulate the decay degree of taxi travel demand in each block. When a major public health event occurs, the residential panic levels in different functional blocks may vary. It results in variable changing speeds of residential travel demand in each block. Based on this assumption, we use the intensity of travel demand as a correlation strength factor between blocks, and equate it with the technical coefficient in the DIIM model. We also define other variables to serve in model construction. These variables include the decay degree of travel demand intensity, residential travel willingness, coefficient of travel demand decay, derivative coefficient of travel demand interdependency, and demand perturbation coefficient. Lastly, we select a central area of Ningbo as the study area, and use taxi travel data in Ningbo during the COVID-19 pandemic of 2020 as input, simulate taxi travel demand dynamics, and analyze the accuracy and sensitivity of the model parameters. The relative errors between the five types of blocks and the actual decay of travel demand intensity are 8.3%, 3.8%, 8.7%, 5.5%, and 5.3%, respectively, which can basically match the actual situation, proving the validity of the model. The results of the study reveal the pattern of taxi travel demand decay among various blocks after major public health events. It provides methodological reference for decision makers to understand the development trend of multi-block taxi travel demand, so as to help form effective emergency plans for different blocks.

Human movement patterns of farmers and forest workers from the Thailand-Myanmar border

Background: Human travel patterns play an important role in infectious disease epidemiology and ecology. Movement into geographic spaces with high transmission can lead to increased risk of acquiring infections. Pathogens can also be distributed across the landscape via human travel. Most fine scale studies of human travel patterns have been done in urban settings in wealthy nations. Research into human travel patterns in rural areas of low- and middle-income nations are useful for understanding the human components of epidemiological systems for malaria or other diseases of the rural poor. The goal of this research was to assess the feasibility of using GPS loggers to empirically measure human travel patterns in this setting, as well as to quantify differing travel patterns by age, gender, and seasonality. Methods: In this pilot study we recruited 50 rural villagers from along the Myanmar-Thailand border to carry GPS loggers for the duration of a year. The GPS loggers were programmed to take a time-stamped reading every 30 minutes. We calculated daily movement ranges and multi-day trips by age and gender. We incorporated remote sensing data to assess patterns of days and nights spent in forested or farm areas, also by age and gender. Results: Our study showed that it is feasible to use GPS devices to measure travel patterns, though we had difficulty recruiting women and management of the project was relatively intensive. We found that older adults traveled farther distances than younger adults and adult males spent more nights in farms or forests. Conclusion: The results of this study suggest that further work along these lines would be feasible in this region. Furthermore, the results from this study are useful for individual-based models of disease transmission and land use.